faculty of electrical engineering - aktualności · artificial intelligence, patrick henry winston,...
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FACULTY OF ELECTRICAL ENGINEERING LIST OF COURSES FOR ACADEMIC YEAR 2017/2018
If you have any questions regarding courses please contact person responsible for the course or faculty
coordinator directly.
Course title Person responsible for
the course
Semester
(winter/summer)
ECTS
points
Antennas and EM wave propagation Stanisław Gratkowski winter 3
Artificial Intelligence In Automation and Robotics Krzysztof Jaroszewski winter or summer 3
B.Sc. Thesis winter or summer 15
Basic Course of Metrology Artur Wollek winter 4
Basics of Power Electronics Marcin Hołub winter or summer 3
Biomedical Signal Processing and Analysis Joanna Górecka winter or summer 4
Biomedical Technology Equipment Joanna Górecka winter or summer 3
Computer Animation Przemysław Mazurek winter or summer 4
Computer Graphics and Visualisation Krzysztof Okarma winter or summer 5
Computer Methods for Mathematical Computations Marcin Ziółkowski winter or summer 4
Computer Networks Piotr Lech winter 4
Computer Vision and Image Processing Krzysztof Okarma winter or summer 6
Control of Electric Drives Marcin Hołub winter or summer 4
Control of Mobile Robots Adam Łukomski winter or summer 2
Digital Technique Joanna Górecka winter or summer 4
Electric Power Network Michał Zeńczak winter or summer 3
Electrical Circuit Analysis with Matlab Marcin Ziółkowski winter or summer 3
Electrical Power Engineering Michał Zeńczak winter or summer 6
Electromagnetic Field and the Human Body Stanisław Gratkowski winter or summer 3
Electromagnetic Methods of Non-destructive Testing Tomasz Chady winter or summer 4
Electronic Devices and Circuits Witold Mickiewicz winter or summer 4
Elements of Laser Optics Andrzej Ziółkowski summer 3
Elements of Psychoacoustics and Electroacoustics Witold Mickiewicz winter or summer 4
EM Fields Effects in Living Organisms Michał Zeńczak winter 2
Fiber Optic Access Networks (Foam) Patryk Urban Summer 3
Fiber Optics Instalation Grzegorz Żegliński Winter 3
Fundamentals of Engineering Electromagnetics Stanisław Gratkowski winter or summer 3
Fundamentals of Web Development Przemysław Włodarski winter or summer 5
High Voltage Engineering Szymon Banaszak winter or summer 4
Industrial Electronics PhD Research Lab Marcin Hołub winter or summer 10
Introduction to Control Engineering Paweł Dworak winter or summer 4
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Introduction to Cryptography Maciej Burak winter or summer 3
Introduction to Electric Circuits – part 1 Tomasz Chady winter or summer 4
Introduction to Electric Circuits – part 2 Tomasz Chady winter or summer 4
Introduction to Multisensor Data Fusion Grzegorz Psuj winter or summer 2
Introduction to Sound Recording Technology Witold Mickiewicz winter or summer 4
M.Sc. Thesis winter or summer 20
Machine Learning Adam Krzyżak summer 6
Managing Model-Based Development Krzysztof Pietrusewicz winter or summer 3
Medical Imaging Systems Piotr Okoniewski winter or summer 3
Modeling of Complex Systems with the use of SysML Krzysztof Pietrusewicz winter or summer 3
Modern Electrical Machines Ryszard Pałka winter or summer 6
Multistructured Optical Fibres Applications Ewa Weinert-Rączka winter 2
Network Systems Administration Piotr Lech summer 4
Network Traffic Przemysław Włodarski winter or summer 5
Non-Destructive Testing (NDT) using radiographic (X-ray)
and terahertz method Tomasz Chady winter or summer 4
Nonlinear Control Adam Łukomski winter or summer 3
Object-Oriented Programming in C# Marcin Ziółkowski winter or summer 4
Optimization Theory Marcin Ziółkowski winter or summer 4
Pattern Recognition and Classification Adam Krzyżak summer 4
Power Electronics for Renewable Energy Sources Marcin Hołub winter or summer 3
Power System Engineering Michał Balcerak winter or summer 3
Power system protection Michał Zeńczak winter or summer 2
Problem-Solving Workshop Joanna Górecka winter or summer 5
Programmable Automation System Based on PLC and HMI Krzysztof Jaroszewski winter or summer 3
Programmable Logic Devices Witold Mickiewicz winter or summer 4
Renewable Energy Sources Michał Balcerak winter or summer 2
Requirements Management in Research Projects on Complex
Systems Krzysztof Pietrusewicz winter or summer 3
Robot Dynamics and Control Rafał Osypiuk summer 2
Selected Topics in Nonlinear Photonics Ewa Weinert-Rączka summer 2
Simulation and Design of Power Electronic Converters Marcin Hołub winter or summer 3
Sound System Design Witold Mickiewicz winter or summer 4
Statistical Methods in ICT Przemysław Włodarski winter or summer 5
Telemedicine Sławomir Kocoń winter or summer 3
Terahertz Technique Przemysław Łopato winter or summer 2
Ultrasonic and Radiographic Nondestructive Testing Marcin Ziółkowski winter or summer 2
Visual Programming in LabVIEW Paweł Dworak winter or summer 3
Walking Robots Adam Łukomski winter or summer 3
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Course title ANTENNAS AND EM WAVE PROPAGATION
Field of study Electrotechnics, electronics
Teaching method Lectures with simple experiments;
laboratory –measurements and computer simulations of antenna structures
Person responsible for
the course
Stanisław Gratkowski
(laboratory – Przemyslaw
Lopato)
E-mail address to the
person responsible for
the course
Course code
(if applicable) ECTS points 3
Type of course Obligatory Level of course bachelor/master
Semester Winter Language of instruction English
Hours per week
3 hours
(lectures – 2, laboratory –
1, other organization is
possible)
Hours per semester
45 hours
(lectures – 30,
laboratory – 15)
Objectives of the
course
This course is intended to present foundations of antenna and microwave engineering.
Numerical modeling and measuring techniques are also described.
Entry requirements/
prerequisites Basic course of mathematics and physics (electromagnetics)
Course contents
Electromagnetic waves, Maxwell’s equations, antenna parameters, types of antennas, arrays,
smart antennas, transmission lines, waveguides, reflection coefficient, SWR, impedance
matching, Smith chart, S-parameters, active and passive microwave devices, computer aided
analysis of antennas and microwave instruments (numerical techniques review),
measurements of antennas and microwave devices.
Assessment methods Lectures – written and oral exam; laboratory – continuous assessment
Learning outcomes
During the course, students will gain a basic knowledge of the operation, design and
modeling of antenna and microwave systems utilized in electrotechnics, electronics and
telecommunication.
Required readings
1. Balanis Constantine A., Antenna Theory: Analysis and Design, John Wiley & Sons, 2005
2. Bansal Rajeev, Fundamentals of engineering electromagnetics, CRC Press
Taylor & Francis, 2006
3. Collin Robert E., Foundations for microwave engineering, John Wiley & Sons, 2001
Supplementary
readings
1. Milligan Thomas A., Modern antenna design, John Wiley & Sons, 2005
2. Hong J.S., Lancaster M.J., Microstrip filters for RF/Microwave applications, John Wiley &
Sons, 2001
Additional information -
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Course title ARTIFICIAL INTELLIGENCE IN AUTOMATION AND ROBOTICS
Field of study
Automatic Control and Robotics, Electrical Engineering, Mechanical Engineering,
Management and Production Engineering , Information and Communications Technology,
Electronics and Telecommunications, Architecture and Urban Planning - Civil Engineering
Teaching method Lecture, project, laboratory
Person responsible for
the course Krzysztof Jaroszewski
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) Compulsory/optional ECTS points 3
Type of course Level of course bachelor
Semester Winter or summer Language of instruction English
Hours per week 1 (L) 1 (P) 1 (Lab) Hours per semester 1 (L) 1 (P) 1 (Lab)
Objectives of the
course
To deliver the basic knowledge about artificial intelligence with special focus on genetic
algorithms, neural networks and fuzzy logic. Student achieve competence of using
mentioned methods in task of optimization, modeling, control, recognition and
classification – Matlab environment.
Entry requirements/
prerequisites Elementary knowledge in the subject of Mathematics and Physics
Course contents
Perceptron – decisive boundary. Multilayer neural network – backpropagation learning
algorithm. Recursive neural networks. Selection, crossing and mutation – steps of classical
genetic algorithms and genetic operators. Membership functions, rules editing,
fuzzyfication and defuzzyfication, concluding in expert and fuzzy systems.
Assessment methods Grade
Project work
Learning outcomes Ability to define basic subjects connected with artificial intelligence. Skills in implementing
and using proper method of artificial intelligence.
Required readings
Curse materials
Manuals of Matlab/Simulink environment
Artificial Intelligence: A Modern Approach, Stuart Russell, Peter Norvig, ISBN 0136042597
Supplementary
readings
1. Artificial Intelligence, Patrick Henry Winston, ISBN: 0201533774
2. Artificial Intelligence: A New Synthesis, Nils J. Nilsson, ISBN: 1558604677
Additional information Max 12 persons.
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Course title B.Sc. Thesis
Teaching method Individual work with the thesis supervisor
Person responsible for
the course
Depends on the subject of the
thesis
E-mail address to the person
responsible for the course
Course code
(if applicable) ECTS points 15
Type of course Obligatory Level of course bachelor
Semester Winter or summer Language of instruction English
Hours per week Hours per semester 12 hours
Objectives of the
course
This course is intended to help students with their B.Sc. thesis. The work is either a project
or a research. It can result in e.g. creating a computer program, laboratory work station, a
device-model or presenting results of research carried out using professional devices or
programs.
Entry requirements/
prerequisites
- Knowledge of basic issues related to the subject of the thesis
- Ability to formulate technical texts and prepare drawings and diagrams presenting
gained results
Course contents
Doing a B.Sc. thesis is in fact realization of a typical engineering task that starts with
formulating a problem and making assumptions, analyzing current state of the art and
defining the method of realizing the aim of the work. At the end of the task, the student
formulates conclusions and prepares written description of performing the task, its results
and analysis.
Assessment methods Continuous assessment and instructions given by the supervisor
Learning outcomes
Knowledge of modern solutions related to the subject of the thesis, ability to write technical
reports and prepare related multimedia presentations, ability to find the necessary
information in the literature and technical documentation
Recommended
readings Depends on the subject of the thesis
Additional information Please contact the faculty Erasmus coordinator to discuss the details of the course.
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Course title BASIC COURSE OF METROLOGY
Field of study Electrical Engineering
Teaching method Lecture / laboratory
Person responsible for
the course Artur Wollek
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course compulsory Level of course bachelor
Semester winter Language of instruction English
Hours per week 1 L / 2 Lab Hours per semester 15 L / 30 Lab
Objectives of the
course
To provide a basic knowledge in the field of metrology. The student learns: typical methods
of measurement methods and tools necessary for analyzing the results of the
measurements, as well as the current state and development trends in the field of sensors,
transducers and measurement systems.
Entry requirements/
prerequisites Mathematics, Physics
Course contents
Basic concepts of metrology, units and the measurement system, measurement standards.
Measuring scales. Basic methods of measurement. Analysis of accuracy of measurement:
systematic and random errors, the uncertainty of measurement. Electrical quantities
measurement. Measurement of voltage and current. Measurement of resistance and
impedance. Non-electrical quantities measurement. Measurement of the frequency, period
and time. Classification of sensors and transducers for measuring non-electrical values.
Static and dynamic properties of sensors and transducers. Temperature measurement
methods. Measurement of rotational speed. Pressure measurements. Measurement of the
magnetic properties of solids. Measuring systems. ADC and DAC converters – structure, the
principle of operation, properties. DAQ cards in measuring systems. Interfaces in measuring
systems. Software of the measurement systems.
Assessment methods Lectures – written exam / Laboratory – continuous assessment
Learning outcomes
The student can choose the typical measurement methods and appropriate sensors and
transducers, as well as to assess the usefulness of new solutions for the implementation of
the tasks associated with electrical engineering.
Required readings
1. Evaluation of measurement data – Guide to the expression of uncertainty in
measurement, JCGM, 2008
2. Northrop R.B.: Introduction to instrumentation and measurements, CRC Press, 2005
3. Sidor T.: Electrical and Electronic Measurement and Instrumentation, AGH, 2006
4. Sydenham P.H.: Handbook of Measurement Science, John Wiley & Sons Ltd., 1983
5. The Metrology Handbook, ASQ Quality Press, 2004
6. Tumański S.: Principles of electrical measurement, Taylor&Francis Group, 2016
Supplementary
readings
1. Bewoor A.K., Kulkarni V.A.: Metrology&Measurements, Tata McGraw-Hill, 2009
2. Kularatna N.: Digital and analogue instrumentation testing and measurement, IEE, 2004
Additional information
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Course title BASICS OF POWER ELECTRONICS
Field of study Electrical engineering, automatic control systems, industrial electronics, mechatronics
Teaching method lecture /laboratory
Person responsible for
the course Marcin Hołub
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 3
Type of course Obligatory Level of course bachelor
Semester winter or summer Language of instruction English
Hours per week 1L/2Lab Hours per semester 15 L
30 Lab
Objectives of the
course
Student will be able to:
- distinguish basic types of power semiconductors.
- calculate basic losses and cooling requirements.
- distinguish basic rectifier topologies and their main properties,
- draw basic waveforms for different types of loads.
- distinguish basic types of AC/AC converters.
- give basic properties and characteristics for main types of switched mode power
supplies.
- perform basic calculations for main circuit components and adjust component
type and kind.
- use CAD software for basic simulations and basic types of projects.
- perform basic project for a small scale power converter.
- analyze basic structures of power converters.
Entry requirements/
prerequisites Electronics, basics of electrical engineering
Course contents
Power electronics: past and present, perspectives, connections with other technical
branches Semiconductor power devices: thyristors (SCR, GTO, IGCT), power transistors (BJT,
MOSFET, IGBT). Power modules. ontrol of semiconductor power devices, power transistor
driving stages Static and dynamic losses of power semiconductors. Thermal characteristics,
cooling methods. Over-voltage, over-current and short-circuit protection systems Rectifiers
– one phase, three phase. Characteristics under resistive, RL and RLE load. Controlled
rectifiers – thyristor rectifiers with the 4T and 6T topology. Characteristics under resistive, RL
and RLE load. Hard switching DC/DC choppers, single and three-phase. Boost and
buck/boost converters, smps systems topologies, basics of magnetics and design of chokes
and HF transformers. Transistor inverters – single and three-phase topology. Methods of
voltage and current shaping (PWM,SVM, harmonics elimination). Special converters (PFC, E-
class). Electric drive converter systems, power electronics for photovoltaic and wind energy
conversion.
Assessment methods
Written tests
Project work assessment
Laboratory reports
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Learning outcomes
Ability to distinguish properties of power semiconductors. Ability to define and measure
basic waveforms and characteristics of AC/DC, AC/AC, DC/DC and DC/AC converters. Ability
to analyze and choose converter topology. Basic knowledge on converter construction.
Basic knowledge on converter simulation
Required readings
1. K. Billings, T. Morey, Switching power supply design, ISBN 978-0-07-148272-1McGrawHill
2009
2. K. Billings, Switchmode power supply handbook, ISBN 0-07-006719-8McGrawHill 1999
3. M. H. Rashid, Power Electronics Handbook, Elsevier 2007, ISBN-13: 978-0-12-088479-7
Supplementary
readings
Additional information
Course title BIOMEDICAL SIGNAL PROCESSING AND ANALYSIS
Field of study
Teaching method lectures, labs (also in hospital), project
Person responsible for
the course Joanna Górecka
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course compulsory Level of course bachelor or master
Semester winter or summer Language of instruction English
Hours per week 3 (1L, 1Lab, 1P) Hours per semester 45 (15L, 15Lab, 15P)
Objectives of the
course
To provide up to date knowledge on methods and techniques used in acquisition,
processing and analysis of biosignals and to develop practical skills useful in this field.
Entry requirements/
prerequisites Mathematics, signal processing.
Course contents
Lectures: Biosignals: definitions, classification. Methods and techniques of biosignal
acquisition, processing and analysis. Biosignal analysis in time and frequency domain.
Chosen methods of statistical biosignal analysis. MATLAB and LabView environments in
biosignal processing and analysis, dedicated toolboxes.
Labs: Chosen biosignals analysis using software tools: MATLAB, LabView.
Project: Using computer tools in processing and analysis of biological signals, implementing
algorithms applied to different biosignals.
Assessment methods Written exam, accomplishment of practical labs and project work.
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Learning outcomes
The student has knowledge on methods and techniques used in acquisition, processing and
analysis of biomedical signals as well as on research methodology used in this field. He has
practical skills useful in this area regarding bio-measurements (instrumentation, specialized
software tools).
Required readings
1. Bronzino J. D. (ed.): Biomedical Engineering Handbook, CRC Press, IEEE Press, 1995.
2. Oppenheim, A.V. and Schafer W.: Discrete-time signal processing, Prentice Hall, 1999.
3. Cohen L.: Time-frequency analysis, 1995.
4. Qian S., Chen D.: Joint time-frequency analysis. Methods and Applications, Prentice-Hall,
1996.
Supplementary
readings Eugene N. Bruce: Biomedical Signal Processing and Signal Modeling, Wiley, 2001.
Additional information -
Course title BIOMEDICAL TECHNOLOGY EQUIPMENT
Field of study
Teaching method lectures, labs (also in hospital)
Person responsible for
the course Joanna Górecka
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 3
Type of course compulsory Level of course bachelor or master
Semester winter or summer Language of instruction English
Hours per week 1L/2Lab Hours per semester 15L/30Lab
Objectives of the
course
To provide basic knowledge on biomedical technology: instrumentation, equipment,
specialized systems, and to develop practical skills useful in this area of engineering.
Entry requirements/
prerequisites Mathematics, Physics, Informatics, fundamentals of semiconductor electronics.
Course contents
Lectures: Biomeasurements, biomedical instrumentation, biosignals (1-D, 2-D) acquisition.
Equipment: ECG, EEG, EMG, VEP/P300, biofeedback and neurofeedback system. Typical
medical imaging systems. Medical telematics, IT in e-Health. Computer aided medical
diagnosis. Assessment of biomedical devices and technologies.
Labs: Biosignals and biomeasurements. Biosignal acquisition, processing and analysis using
specialized transducers, amplifiers and equipment.
Assessment methods Lectures: grade, accomplishment of lab tasks.
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Learning outcomes
The student has basic knowledge on biomedical technology (instrumentation, equipment,
software, specialized systems and standards used in this field). He has practical skills useful
in the area of biomedical technologies regarding their development, implementation,
exploitation and assessment.
Required readings
1. Bronzino J. D. (ed.): Biomedical Engineering Handbook, CRC Press, IEEE Press, 1995.
2. Bemmel, van J. H., Musen M. A.: Handbook of Medical Informatics, Bohn Stafleu Van
Loghum, Springer, 1997.
3. Christensen D. A.: Ultrasonographic Bioinstrumentation, J. Wiley & Sons, N.Y., 1988.
Supplementary
readings Huang H. K.: PACS in Biomedical Imaging. VCH Publ. Inc., N.Y., 1996.
Additional information -
Course title COMPUTER ANIMATION
Field of study Control Engineering & Robotics, Teleinformatics, Electronics & Telecommunications
Teaching method Lecture / laboratory
Person responsible for
the course
Przemysław Mazurek
Dr Eng Sc
E-mail address to the
person responsible for the
course
Course code
(if applicable) ECTS points 4
Type of course optional Level of course bachelor
Semester winter or summer Language of instruction english
Hours per week 2W 2L Hours per semester 30W, 30L
Objectives of the
course
Basic knowledge about 3D graphics and applications using software tools. Practical aspects
of computer animation.
Entry requirements/
prerequisites -
Course contents 3D modeling, 3D synthesis of objects, rendering techniques, lighting, textures, keyframe
animation, human body modeling and animation, morphing
Assessment methods
grade
training
project work
Learning outcomes Knowledge about: 3D computer animation , special effects, film production
Required readings Blender, e-on Vue, Adobe Photoshop tutorials
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Supplementary
readings -
Additional information -
Course title COMPUTER GRAPHICS AND VISUALISATION
Field of study ICT
Teaching method Lecture + project
Person responsible for
the course Krzysztof Okarma
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 5
Type of course optional Level of course bachelor
Semester winter or summer Language of instruction English
Hours per week 2 Lecture / 2 project Hours per semester 30 Lecture / 30 project
Objectives of the
course
This course is intended to present fundamental algorithms in computer graphics as well as
some advanced techniques used in image synthesis
Entry requirements/
prerequisites
Fundamentals of computer engineering, mathematics (a short introduction to 3-D
geometry is provided)
Course contents
Digital image – classes, representations and conversion methods. Characteristics and
parameters of computer images. Raster and vector graphics. Methods of line drawing in
raster computer graphics. Bresenham’s algorithm. Polygon triangulation methods.
Techniques of area’s filling in raster images. Geometric operations on raster images in two-
dimensional and 3-D spaces. Visualisation of 3-D figures. Field of view. Virtual camera
model used in computer graphics. Algorithms for surfaces’ visibility detection. Depth buffer.
Texturing methods. Modelling of smooth shapes and surfaces. Applications of fractals in
computer graphics. Data structures used in computer graphics. Methods of colours’
representing (colour spaces). Graphic file formats. Basics of OpenGL standards –
specification and properties. 3-D images synthesis methods. Light modelling and shading
methods. Ray-tracing and radiosity methods in computer visualisation.
Assessment methods Written exam (test) / project work
Learning outcomes Knowledge of fundamentals of computer graphics. Ability to utilize some computer
graphics algorithms and/or applications for computer visualisation purposes.
Required readings
1. Foley J.D. et al: An Introduction to Computer Graphics. Addison-Wesley, 2000.
2. Pavlidis T.: Algorithms for Graphics and Image Processing, Computer Science Press,
Rockville, 1982
Supplementary
readings
1. Yun Q. Shi, Huifang Sun: Image and Video Compression for Multimedia Engineering -
Fundamentals, Algorithms and Standards.
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CRC Press 2000.
2. Ling Guan, Sun-Yuan Kung, Larsen J.: Multimedia Image and Video Processing. CRC Press
2001.
Additional information
Course title COMPUTER METHODS FOR MATHEMATICAL COMPUTATIONS
Field of study Electrical Engineering, Computer Engineering, Electronic Engineering, Information
Technology Engineering, Automation and Robotics Engineering
Teaching method Lectures, Laboratory
Person responsible for
the course Marcin Ziółkowski
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course Obligatory Level of course Bachelor
Semester Winter or summer Language of instruction English
Hours per week Lectures - 2
Laboratory - 2 Hours per semester
Lectures - 30
Laboratory – 30
Objectives of the
course
This course is intended to present a unified approach to various numerical methods in
Matlab environment.
Entry requirements/
prerequisites Mathematics
Course contents
1. Floating-Point Arithmetic
2. Linear Equations
3. LU Factorization
4. Effect of Roundoff Errors
5. Norms and Condition Numbers
6. Sparse Matrices and Band Matrices
7. PageRank and Markov Chains
8. Interpolation
9. Zeros and Roots
10. Least Squares
11. Curve Fitting
12. Quadrature
13. Ordinary Differential Equations
14. Fourier Analysis
15. Random Numbers
16. Eigenvalues and Singular Values
17. Inverse Problems in Engineering
Assessment methods Lectures – written exam; Laboratory – continuous assessment
Learning outcomes Students will get the knowledge about applying computer methods for solving
mathematical problems.
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Required readings
1. S. Moler: Numerical Computing with Matlab, electronic edition, The MathWorks, Inc.,
Natick, MA, 2004
2. G. Forsythe, M. Malcom, C. Moler: Computer Methods for Mathematical Computations,
Prentice-Hall, Englewood Cliffs, NJ, 1977
Supplementary
readings Per Christian Hansen: Regularization Tools, Technical University of Denmark, Lyngby, 2008
Additional information
Course title COMPUTER NETWORKS
Field of study ICT
Teaching method Lecture / laboratory
Person responsible for
the course Piotr Lech
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course obligatory Level of course bachelor
Semester winter Language of instruction English
Hours per week 1 Lecture / 2 Lab. Hours per semester 15 Lecture /
30 Laboratory
Objectives of the
course
This course introduces the fundamental problems of computer networking, from sending
bits over wires to running distributed applications. Topics include error detection and
correction, multiple-access, bandwidth allocation, routing, internetworking, reliability,
quality of service, naming, content delivery, and security.
Entry requirements/
prerequisites Prerequisites and additional requirements not specified
Course contents
Introduction: to Network Models, Protocols and Layering, Physical and Link layers,
Retransmissions, Multiple access, Switching , Network layer, Internet working, Routing,
Internet protocol suite , Transport layer, Reliability , Congestion Control, DNS, Web/HTTP,
Content Distribution, Quality of Service and Real-time Apps Network Security , Client-server
and peer-to-peer architectures.
Assessment methods Written exam (test), continuous assessment (laboratory)
Learning outcomes
Knowledge of basic configuration of computer networks and IP networks .Addressing in
computer networks. Understanding of layered models in networking. Understanding of
protocols'
Required readings
1. Carla Schroder Linux Networking Cookbook O'Reilly Media 2007 ISBN: 978-0-596-
10248-7 Ciprian Adrian Rusen, 7 Tutorials Network Your Computers & Devices Step by
Step Microsoft Press 2010 ISBN: 978-0-7356-5216-3
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Supplementary
readings Selected RFC documents.
Additional information
Course title COMPUTER VISION AND IMAGE PROCESSING
Field of study ICT
Teaching method Lecture + project
Person responsible for
the course Krzysztof Okarma
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 6
Type of course optional Level of course bachelor
Semester winter or summer Language of instruction English
Hours per week 2 Lecture / 2 project Hours per semester 30 Lecture / 30 project
Objectives of the
course
This course is intended to present a unified approach to image processing techniques with
introduction to image analysis and basics of computer visualisation
Entry requirements/
prerequisites
Basic knowledge of Matlab or Mathcad environments,
basic knowledge about programming and signal processing
Course contents
Digital image – classes, representations and conversion methods. Colour models. Arithmetic
and logic operations on digital images. Geometric operations, matrix notation. Digital
image acquisition. Local processing and filtration using convolution filters. Methods for
reduction of the number of colours. Deformations, bilinear projection and morphing.
Frequency-based image processing methods. Histogram and histogram-based operations.
Binarization. Morphological operations. Image segmentation. Indexing techniques in image
processing. Measuring methods using image analysis. Lossy and lossless image
compression standards. Image and video quality assessment methods. Nonlinear filtration
of colour images. Basics of photogrammetry and 3D Vision. Applications of machine vision
in automation and robotics.
Assessment methods Written exam (test) / project work
Learning outcomes Knowledge of basic image processing and analysis algorithms. Ability to implement some
image processing and basic image analysis algorithms in chosen environment (e.g. Matlab).
Required readings 1. Pratt W.K.: Digital Image Processing (4th Edition). Wiley Interscience, New York 2007.
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Supplementary
readings
1. Foley J.D. et al: An Introduction to Computer Graphics. Addison-Wesley, 2000.
2. Pavlidis T.: Algorithms for Graphics and Image Processing, Computer Science Press,
Rockville, 1982.
3. Nelson M.: The Data Compression Book. IDG Books Worldwide, Inc. 2000.
4. Ritter G.X., Wilson J.N.: Handbook of Computer Vision - Algorithms in Image Algebra.
CRC Press 1996.
5. Russ J.C.: The Image Processing Handbook. CRC Press 1999.
Additional information
Course title CONTROL OF ELECTRIC DRIVES
Field of study Electrical engineering, automatic control systems, industrial electronics, mechatronics,
robotics
Teaching method lecture / laboratory
Person responsible for
the course Marcin Hołub
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course Obligatory Level of course master
Semester winter or summer Language of instruction English
Hours per week 1L/2Lab Hours per semester 15 L /30 Lab.
Objectives of the
course
Student will recognize and distinguish basic properties and parameters of DC motors, will
be able to construct basic motor models. Will understand cascaded control systems, PI
controller operation and basics of controller tuning. Will have an overview of basic
properties of PM excited and series and parallel connected DC machines. Students will
recognize basic properties, characteristics and types of induction machines (IM and DFIG) as
well as types of controllers and control types for induction machines. Students will get
familiar with basics of frequency converter operation and parametrization. Students will
distinguish scalar and vector control. Students will recognize basic properties of permanent
magnet excited machines (PMSM and BLDC) and will be able to draw basic waveforms for
BLDC and PM type machines operation. Students will be able to set up a basic control type
(torque, speed) and frequency converter operation.
Entry requirements/
prerequisites
Basics of electrical engineering, electric machines, basics of automatic control, power
electronics
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Course contents
Overview of basic types of DC machines: auxiallary excited, series and parallel connected.
Mechanical characteristics. DC machines: parameters, models. Automatic control rules,
controller types, basic definitions. Cascaded control: controller tuning using module and
symmetry criterion. Induction machines: construction (IM and DFIG), properties, control
types. Basic scalar control: types, voltage control, frequency control. Vector control: axis
transformation, voltage based control, Blaschke equations, current based methods.
Characteristics and basic properties of different constructions. Control system examples in
Matlab and using Simovert drives. PM excited machines: types, basic properties. BLDC
control systems, vector control strategies for PMSM motors. Drive systems for automobile
applications.
Assessment methods Written exam
Laboratory reports and written tests
Learning outcomes
Ability to calculate and analyze properties of torque, speed and position controller settings
in case of DC – based, Ac – based and PM – based drive systems. Ability to define and
analyze parameters of machines and construct a proper machine model. Practical abilities
on controller setting influence on drive properties, drive system parametrization, inverter
settings.
Required readings
1. M. H. Rashid, Power Electronics Handbook, Elsevier 2007, ISBN-13: 978-0-12-088479-7
2. Bimal Bose, Power electronics and motor drives, Elsevier 2006, ISBN-13 978-0-12-
088405-6
Supplementary
readings
Additional information
Course title CONTROL OF MOBILE ROBOTS
Field of study Automatic Control and Robotics
Teaching method Laboratory course involving simulation of control algorithms for mobile robots, path
planning and experimental verification on wheeled mobile robots.
Person responsible for
the course Adam Łukomski
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 2
Type of course optional Level of course bachelor
Semester Winter or summer Language of instruction english
Hours per week 2h laboratory Hours per semester 30h laboratory
Objectives of the
course
The Student will learn to design and apply nonlinear control to a class of wheeled mobile
robots.
Entry requirements/
prerequisites Linear control, Dynamical systems
17
Course contents
This course covers basic modelling of mobile robots, kinematics and dynamics, nonlinear
control design, path planning and trajectory following. Experimental verification will be
done using a two-wheeled platform (unicycle-like) and miniature car-like robot.
Assessment methods Written exam (on last meeting), Continuous assessment during laboratory course
Learning outcomes Ability to create a kinematic and dynamic model of the mobile robot.
Ability to create, analyse and implement a model-based control system.
Required readings 1. Murray, Richard M., et al. A mathematical introduction to robotic manipulation. CRC
press, 1994.
Supplementary
readings 1. Slotine, Jean-Jacques E., and Weiping Li. Applied nonlinear control. Prentice-hall, 1991.
Additional information
Course title DIGITAL TECHNIQUE
Field of study
Teaching method lectures, lab
Person responsible for
the course Joanna Górecka
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course compulsory Level of course bachelor
Semester winter or summer Language of instruction English
Hours per week 2L/2Lab Hours per semester 30L/30Lab
Objectives of the
course
To provide basic knowledge on digital circuit theory and design and to develop skills in
analysis, testing and designing digital circuits using product data sheets as well as
application notes.
Entry requirements/
prerequisites Mathematics, fundamentals of semiconductor electronics.
18
Course contents
Lectures: Number systems. Binary codes, BCD codes. Basics of binary arithmetic. Automata,
logic circuit, digital circuit – basic definitions. Boolean Algebra, fundamental theorems.
Switching (Boolean) functions, simplification, minimisation. Preparing logic functions with
gates, multiplexers and demultiplexers, ROMs, PLA modules. Digital logic circuit - overview,
comparison, development. Time-dependent circuits, multi-vibrators, generators. Flip-flops,
logic description. Fundamentals of digital functional blocks - modules (combinatorial and
sequential). Digital control system, logic description – algorithms. Basics of
microprogramming technique. Introduction to ASICs, PLD modules – classification,
development
Labs: Switching functions minimisation. Preparing logic functions with gates and different
modules. Logic gates testing (switching functions, static and dynamic characteristics). Flip-
flops, registers and counters testing. Testing time-dependent circuits, multi-vibrators,
generators. Testing arithmetic circuits. Testing memories, input circuits and digital displays.
Assessment methods Written exam, accomplishment of practical lab tasks.
Learning outcomes
The student has knowledge on digital circuit theory, methods and techniques of digital
circuit analysis and synthesis, as well as digital circuit design. He has skills in the field of
analysis, testing and designing digital circuits using product data sheets, application notes
as well as dedicated software tools.
Required readings
1. Beards P. H.: Analog and Digital Electronics. A First Course, II ed., Prentice Hall, 1991.
2. Nelson V. P., Nagle H. T., Carroll B. D., Irwin I. D.: Digital Logic Circuit Analysis and
3. Design, Prentice Hall, New Jersey, 1995.
Supplementary
readings 1. Burger P.: Digital Design. A Practical Course, John Wiley & Sons, New York, 1998.
Additional information -
Course title ELECTRIC POWER NETWORK
Field of study Electrical engineering
Teaching method Lecture/project
Person responsible for
the course Michal Zeńczak
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 3
Type of course Obligatory/elective Level of course Bachelor
Semester Winter or summer Language of instruction English
Hours per week 1/1 Hours per semester 15/15
Objectives of the
course
Knowledge: about structure and functioning of electric power networks in normal and fault
conditions.
Skills: of designing of overhead lines and basic calculation for wires.
19
Entry requirements/
prerequisites Basis of electrical engineering, mathematics, physics.
Course contents
Structure of electrical power network, requirements for networks, quality of energy, towers
and wires, current-carrying capacity of wires, HTLS wires, standards for designing of
overhead transmission lines, cable lines, environmental problems.
Assessment methods Project work, final test on the end of lectures.
Learning outcomes
Knowledge: Student has knowledge for analysis of functioning and designing of electrical
power network.
Skills: Student is able to design electrical power network.
Required readings
Supplementary
readings
1. Kiessling F., Nefzger P., Nolasco J.F., Kaintzy U.: Overhead Power Lines, Springer, 2002
2. Grainger J.J., Stevenson W.D.: Power System Analysis, McGAW-HILL
3. INTERNATIONAL EDITIONS, 1994,
4. Grigsby L.L.: The Electric Power Engineering Handbook, CRC PRESS, 1998,
5. Grigsby L.L.: Electric Power Generation, Transmission, and Distribution, CRC PRESS,
2007,
6. Saccomanno F.: Electric Power Systems, Analysis and Control, John Wiley&Sons, 2003,
7. Weedy B.M., Cory B.J.: Electric Power Systems, John Wiley&Sons, 1998,
8. Northcote-Green J., Wilson R.: Control and Automation of Electrical Power Distribution
Systems, Taylor&Francis, 2007
Additional information
Course title ELECTRICAL CIRCUIT ANALYSIS WITH MATLAB
Field of study Electrical Engineering, Computer Engineering, Electronic Engineering, Information
Technology Engineering
Teaching method Lectures, Laboratory
Person responsible for
the course Marcin Ziółkowski
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 3
Type of course Obligatory Level of course Bachelor, Master
Semester Winter or summer Language of instruction English
Hours per week Lectures - 1
Laboratory - 2 Hours per semester
Lectures - 15
Laboratory – 30
Objectives of the
course
This course is intended to present a modern approach to electrical circuit simulation and
analysis using numerical method based on Matlab environment.
20
Entry requirements/
prerequisites Numerical Methods, Mathematics, Physics
Course contents
1. DC Analysis
2. Transient Analysis
3. Network Equations
4. Solution of Linear Algebraic Circuit Equations
5. Solution of Nonlinear Algebraic Circuit Equations
6. Solution of Differential Circuit Equations
7. Application to Circuit Simulation
8. Operational Amplifiers
9. Transistor Circuits
Assessment methods Lectures – written exam; Laboratory – continuous assessment
Learning outcomes Students will get the knowledge about electrical circuits’ simulations methods based on
network approach.
Required readings 1. John O. Attia: Electronics and circuit analysis using Matlab, CRC Press LLC, 1999
2. Farid N. Najm: Circuit simulation, A John Wiley & Sons, Inc, 2010
Supplementary
readings 1. Steven T. Karris: Circuit analysis with Matlab applications, Orchard Publications, 2003
Additional information
Course title ELECTRICAL POWER ENGINEERING
Field of study Electrical engineering
Teaching method Lecture, laboratory, classes.
Person responsible for
the course Michał Zeńczak
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 6
Type of course Obligatory/elective/
optional Level of course Bachelor
Semester Winter or summer Language of instruction English
Hours per week 2/1/1 Hours per semester 30/15/15
Objectives of the
course
Knowledge about composition and operation of power system,
Skills of calculation in power system: load flows, short-circuits,
Skills of investigation of basic phenomena in power system.
Entry requirements/
prerequisites Basis of electrical engineering, mathematics, physics.
21
Course contents
Composition of power system, methods of generation of electrical energy, power stations,
equivalent diagrams, voltage loss and voltage drop, vector diagrams, load flow study,
power losses, control of active power and frequency, control of voltage and reactive power,
basic interferences in power system, calculation of load flow study, calculation of voltage
losses and drops, calculation of short-circuits currents, measurements of currents and
voltages in power system, measurements of voltage drops, investigation of radial networks,
investigation of voltage control in power system, investigation of short-circuits,
investigation of non-homogeneous network.
Assessment methods Continuous assessment in laboratory, final test on the end of classes and lectures
Learning outcomes
Knowledge:
Student has knowledge for understanding processes of generation of electrical energy,
Student has knowledge for basic calculation in power system,
Skills:
Student is able to calculate different state in power system.
Required readings
Supplementary
readings
1. Freris L., Infield D.: Renewable Energy in Power Systems, John Wiley&Sons, 2008,
2. Grainger J.J., Stevenson W.D.: Power System Analysis, McGAW-HILL
3. INTERNATIONAL EDITIONS, 1994,
4. Grigsby L.L.: The Electric Power Engineering Handbook, CRC PRESS, 1998,
5. Grigsby L.L.: Electric Power Generation, Transmission, and Distribution, CRC PRESS,
2007,
6. Saccomanno F.: Electric Power Systems, Analysis and Control, John Wiley&Sons, 2003,
7. Weedy B.M., Cory B.J.: Electric Power Systems, John Wiley&Sons, 1998,
8. Northcote-Green J., Wilson R.: Control and Automation of Electrical Power Distribution
Systems, Taylor&Francis, 2007
Additional information
Course title ELECTROMAGNETIC FIELD AND THE HUMAN BODY
Field of study Electrical engineering
Teaching method Lectures, laboratory – computer simulations
Person responsible for
the course
Stanisław Gratkowski,
Katarzyna Cichoń
(lab – Krzysztof Stawicki)
E-mail address to the
person responsible for
the course
Course code
(if applicable) ECTS points 3
Type of course Optional Level of course Bachelor/master
Semester Winter or summer Language of instruction English
22
Hours per week 2L/1 Lab, other
organization is possible Hours per semester 30L/15Lab
Objectives of the
course
To provide up to date knowledge on analysis and modeling of EM fields in the human body,
and to develop practical skills in this area
Entry requirements/
prerequisites Mathematics, physics
Course contents
Basic concepts of electric and magnetic fields; Maxwell’s equations; electromagnetic waves;
dosimetry; numerical modeling of electromagnetic field in the human body; magnetic
induction tomography and magnetoacoustic tomography with magnetic induction for
biomedical applications; examples of medical applications of electromagnetic fields;
biological effects of electromagnetic fields; magnetic resonance imaging (MRI)
Assessment methods Lectures – written and oral exam; laboratory (computer simulations) – continuous
assessment
Learning outcomes On successful completion of this course students will have knowledge on methods for
analysis and modeling of EM fields in living systems and practical skills useful in this area.
Required readings
1. Durney C.H.: Basic Introduction to Bioelectromagnetics. CRC Press LLC, Boca Raton 2000
2. Sadiku M.N.O.: Numerical Techniques in Electromagnetics. CRC Press LLC, Boca Raton
2001
3. IEEE Transactions on Biomedical Engineering
4. Malmivuo J., Plonsey R.: Bioelectromagnetism. Oxford University Press, New York 1995
Supplementary
readings
Additional information
Course title ELECTROMAGNETIC METHODS OF NON-DESTRUCTIVE TESTING
Field of study Electrical engineering, Mechanical engineering, Automatics
Teaching method Lecture and experimental laboratory
Person responsible for
the course
Tomasz Chady
Przemysław Łopato
Grzegorz Psuj
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course Obligatory Level of course Bachelor, Master
Semester winter or summer Language of instruction English
Hours per week 3L / 2Lab Hours per semester 45L / 30Lab
Objectives of the
course
To give basic knowledge of techniques for non-destructive testing (NDT),
To teach how to apply specific method in practical applications,
To give students an understanding of NDT by comparing the major evaluation
23
methods,
To introduce modern systems and techniques for NDT
Entry requirements/
prerequisites
Academic course of mathematics and physics (required)
Academic course of electrotechnics (suggested)
Course contents
Non-destructive testing - the introduction, the basic idea, the historical background
Review of different methods of non-destructive testing
Transducers for measuring magnetic fields
Non-destructive testing using Barkhausen noise
Method of flux leakage
Eddy current method
Evaluation of low conductivity materials using electromagnetic waves of high frequency
(THz – terahertz TDS imaging)
Computer and digital radiography
Numerical modeling in NDT
The algorithms of digital signal processing in NDT
Algorithms for identification in NDT
Data fusion algorithms
Computer systems in NDT
Industrial tomography
Overview of commercial non-destructive testing systems
Overview of standards used in NDT
Laboratory experiments for selected topics.
Assessment methods Written exam (Lect.) + Continuous assessment (Lab)
Learning outcomes
Upon successful completion of the course, the student will be able to:
identify, formulate, and solve engineering problems in the field of NDT,
explain the principles of the major NDT methods,
identify advantages and limitations of nondestructive testing methods and to select the
appropriate techniques for inspections in specific application,
use selected software for numerical modelling of NDT systems,
use selected hardware for practical NDT (i.e. THz TDS or digital detectors for X-ray
testing,
critically evaluate their chosen problem solving techniques and the accuracy of their
answers.
Required readings 1. Hellier C. J., Handbook of Nondestructive Evaluation, McGrown-Hill, 2003
Supplementary
readings
1. Blitz. J., Electrical And Magnetic Methods of Non-Destructive Testing, Springer-Verlag,
1997
2. Mester M. L., McIntire P, Nondestructive Testing Handbook Volume 4 Electromagnetic
Testing, ASNT, 1996
3. Jiles D. C., Introducting to Magnetism and Magnetic Materials, Springer, 1990
4. Sakai K., Terahertz Optoelectronics, Springer-Verlag Berlin Heidelberg 2005
5. Tumanski, S., Principles of electrical measurement, Taylor & Francis Group, 2006
Additional information Maximum number of students in case of the laboratory group: 10
24
Course title ELECTRONIC DEVICES AND CIRCUITS
Field of study
Electronics and Telecommunications
Automatic Control and Robotics
Electrical Engineering
Teaching method lectures, lab
Person responsible for
the course Witold Mickiewicz
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course Compulsory / optional Level of course bachelor
Semester winter or summer Language of instruction English
Hours per week 2L/2Lab Hours per semester 30L/30Lab
Objectives of the
course
To provide knowledge on electronic semiconductor devices selected topics on analog
electronic circuits.
Entry requirements/
prerequisites Mathematics, physics.
Course contents
Lectures:
Conduction in semiconductors. Semiconductor-diode characteristics. BJT characteristics.
Transistor biasing and thermal stabilization. Small-signal low-frequency transistor model.
Low-frequency transistor amplifier circuits. The high-frequency transistor. Field-effect
transistors. Integrated circuits. Operational amplifiers. Feedback amplifiers and oscillators.
Active filters circuits. Large-signal amplifiers. Optoelectronics devices. Rectifier and power
supplies.
Labs:
Static and dynamic characteristics of diodes and transistors. Bipolar transistor biasing and
stabilization of operating point. Transistor amplifiers. Applications of operational amplifiers.
Active filters. Oscillators. Rectifiers. Electronic voltage regulators. DC voltage stabilizers.
Assessment methods Written exam, accomplishment of practical lab tasks.
Learning outcomes
The student has knowledge on basic electronic devices and circuit, methods and techniques
of analog circuit analysis. He has skills in the field of analysis, testing and designing simple
electronic circuits using product data sheets, application notes as well as dedicated software
tools.
Required readings 1. Boylestad R.L., Nashelsky L.: Electronic devices and circuit theory, Eleventh edition,
Pearson 2013.
Supplementary
readings 1. Roland E. Thomas: The Analysis and Design of Linear Circuits, 7th Edition, Wiley 2012
Additional information -
25
Course title ELEMENTS OF LASER OPTICS
Field of study Electronics and Telecommunications, Teleinformatics, Automatic Control and Robotics,
Electrical Engineering
Teaching method Lecture + Laboratory
Person responsible for
the course Dr Andrzej Ziółkowski
E-mail address to the
person responsible for the
course
Course code
(if applicable)
ECTS points 3
Type of course facultative Level of course master
Semester summer Language of instruction English
Hours per week 1h-lecture, 1h-project Hours per semester 15h—lecture
15h-project
Objectives of the
course
The first objective of this course is to give basic optics and photonics concepts related to
laser physics.
Entry requirements/
prerequisites Basics knowledge in mathematics and physics
Course contents
Elements of laser optics: Topics related to the basics of laser physics. In particular issues
related to the absorption and emission of light, laser linewidth, pumping processes, optical
amplifiers and optical resonators. Moreover, we will discuss construction and operation of
selected types of lasers such as: gas lasers, semiconductor lasers, solid state lasers.
Assessment methods Lecture, laboratory and numerical simulations
Learning outcomes At successful completion of this course the students will be familiar with main properties of
lasers and other optoelectronic devices
Required readings
1. William T. Silfvast, Laser Fundamentals, Cambridge University Press, 2004
2. E. Rosencher, B. Vinter, "Optoelectronics", Cambridge Univ. Press, Cambridge 2002
3.B. E. A. Saleh, M. C. Teich, Fundamentals of Photonics, Wiley Series in Pure and Applied
Optics, 2007
Supplementary
readings
Additional information
Course title ELEMENTS OF PSYCHOACOUSTICS AND ELECTROACOUSTICS
Field of study Electronics and Telecommunications, Automatic Control and Robotics, Electrical Engineering
Teaching method lectures, seminar, laboratory
26
Person responsible for
the course Witold Mickiewicz
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course optional Level of course bachelor, master
Semester winter or summer Language of instruction english
Hours per week 1L/1S/2Lab Hours per semester 15L/15S/30Labs
Objectives of the
course
To provide knowledge on psychoacoustics basics and selected topics on electroacoustics
(sound fields, transducers, sound reinforcement, sound processing).
Entry requirements/
prerequisites Basic knowledge in Physics
Course contents
Lectures: Sound waves properties. Human auditory system. Musical sounds, notes and
harmony. Elements of psychoacoustics – monaural and binaural hearing effects. Spatial
hearing. Fundamentals of room acoustics and perceiving sound in different environments.
Elements of building acoustics. Electroacoustical transducers and electroacoustical systems.
Hearing aids. Digital sound processing. Audio compression. HRTF technology and 3-D
audio systems.
Seminar: complementary calculation exercises
Labs: Models of human auditory system. Experiments in hearing. Hearing aids, software
support. MATLAB in processing, compression and enhancement of audio signal. 3-D audio
enhancements of 2-channel sound. Loudspeaker parameters identification. Microphones
parameters measurement. Reverberation time measurement. Sound isolation measurement.
Filtering, sound effects.
Assessment methods Written exam, accomplishment of practical labs
Learning outcomes The basic knowledge on psychoacoustics and selected topics on acoustics and
electroacoustics. The skills to use and measure basic electroacoustical systems.
Required readings 1. Howard D. H.: Acoustics and psychoacoustics. Focal press, 2001.
2. Everest F. A.: Master handbook of acoustics. McGraw-Hill, 2001.
Supplementary
readings
1. Blauert J.: Spatial Hearing - Revised Edition: The Psychophysics of Human Sound
Localization. MIT Press, 1999.
Additional information
Course title EM FIELDS EFFECTS IN LIVING ORGANISMS
Field of study Electrical engineering
Teaching method Lecture/laboratory
Person responsible for
the course Michał Zeńczak
E-mail address to the person
responsible for the course [email protected]
27
Course code
(if applicable) ECTS points 2
Type of course Optional Level of course Master
Semester Winter Language of instruction English
Hours per week 1/1 Hours per semester 15/15
Objectives of the
course
To provide up to date knowledge on bioelectromagnetism, electromagnetic fields in natural
environment and interaction of living systems with electromagnetic fields. To develop skills
in designing of electric power engineering structures according to standards for
electromagnetic fields in natural and occupational environment.
Entry requirements/
prerequisites Mathematics, physics, theoretical engineering, theory of electromagnetic fields.
Course contents
Basis of theory of electromagnetic fields in application for biology, natural
and technical sources of electromagnetic fields, standards for electromagnetic fields,
electrical properties of living master, electromagnetic fields inside living systems,
mechanism of interaction of non-ionising electromagnetic fields with living systems,
measurements of EM fields, computer simulations in EM fields, designing electric power
engineering structures according to standards for EM fields.
Assessment methods Continuous assessment in laboratory, final test on the end of lectures
Learning outcomes
Knowledge:
Student has knowledge on bioelectromagnetism, electromagnetic fields in natural
environment and interaction of living systems with electromagnetic fields,
Skills:
Student is able to design electric power engineering structures according to standards for
electromagnetic fields in natural and occupational environment.
Required readings
Supplementary
readings
1. Bronzino J.D., Biomedical Engineering Handbook, CRC Press, IEEE Press,, New York, 1995
2. Carstensen E., Biological effects of transmission line fields, Elsevier, New York,
Amsterdam, London, 1987
3. Malmivuo J., Plonsey R., Bioelectromagnetism, Oxford University Press,, Oxford, 1995
4. Polk C., Postow E., CRC Handbook of biological effects of electromagnetic fields, CRC
Press, Boca Raton, Florida, 1986
5. Wadas R.S., Biomagnetism, PWN, Warsaw, 1978
Additional information
Course title FIBER OPTIC ACCESS NETWORKS (FOAN)
Field of study Electronics and Telecommunications, Electrical Engineering, Teleinformatics
Teaching method Lecture, Project and Seminar
28
Person responsible for
the course
Dr Patryk Urban
(Dr Grzegorz Żegliński)
E-mail address to the
person responsible for
the course
Course code
(if applicable) ECTS points 3
Type of course Facultative / Optional Level of course Master
Semester Summer Language of instruction English
Hours per week 2h – Lecture/Seminar
2h – Project Hours per semester
30h – Lecture/Seminar
30h – Project
Objectives of the
course
The primary objective of this course is to obtain fundamental knowledge on FOAN design
rules and factors influencing decisions along the design process. This is to be preceded by
getting familiar with FOAN components as well as architectural and topological options for
FOANs.
The secondary objectives of this course are: to understand the economics of FOANs; to get
familiar with various relevant job profiles through face-to-face networking with
professionals in the field of optical access networks; to exercise students’ presentation skills
by orally reporting their project results.
Entry requirements/
prerequisites
Academic courses: Math, Physics. Moreover, it is recommended that course participants are
familiarized with the basics of fiber optics e.g. through attending the course Fiber Optics
Installation or alike. Although, essentials with this respect will be recalled during the course.
Course contents
1. FOAN Applications: Drivers and Business Needs
2. Bandwidth Requirements in Access Networks and Evolution of Access Networks
3. Generic FOAN Network Planning
4. FOAN Economics and Its Impacts onto FOAN Design
5. FOAN Terminology, Fiber Optic Symbols and FOAN-related Standards
6. Access Network Architectures and Transmission in FOAN
7. Passive Optical Network Essentials and Next Generation FOAN Outlook
8. FOAN Topologies, Components, Subsystems and Devices
9. FOAN Node Positioning
10. FOAN Network Design
Optional: Fiber-To-The Building Design Deep-dive
11. Loss Budget and Passive Optical Network Class
Assessment methods Project report and presentation (seminar)
Learning outcomes
After successful completion of the course, students will possess solid foundation to develop
towards professional in optical access networks. The students will be familiarized with
optical access network architectures, network components, as well as network planning and
designing. It will ensure students’ up-to-date knowledge base with current standards and
standardization projects under development as well as relevant technology roadmaps.
Required readings FTTH Handbook,
http://www.ftthcouncil.eu/documents/Publications/FTTH_Handbook_V7.pdf
Supplementary
readings
1. FTTH Council online resources, http://www.ftthcouncil.eu/resources/key-
publications
2. K. Wang et al., Techno-Economic Analysis of Active Optical Network Migration
Towards the Next Generation Optical Access, IEEE/OSA Journal of Optical
Communications and Networking, vol. 9, no. 4, April 2017, pp. 327-341
3. P. J. Urban et al., Fiber Plant Manager: an OTDR- and OTM-based Passive Optical
Network Monitoring System, IEEE Communications Magazine, vol. 51, no. 2,
February 2013, pp. 9-15
Additional information
Optionally, a couple of visits to local companies involved in fiber optic access networks
businesses will be organized. Moreover, depending on availability, a couple of professionals
from local companies will be invited for guest presentations and discussion on their job
profiles.
29
Course title FIBER OPTICS INSTALATION
Field of study Electronics and Telecommunications , Automatic Control and Robotics, Electrical
Engineering , Teleinformatics
Teaching method Lecture + Laboratory
Person responsible for
the course Dr Grzegorz Zeglinski
E-mail address to the
person responsible for the
course
Course code
(if applicable)
ECTS points 3
Type of course facultative Level of course master
Semester winter Language of instruction English
Hours per week 1h-lecture,
2h-laboratories Hours per semester
15h—lecture
30h-laboratories
Objectives of the
course
The first objective of this course is to give basic
concepts relating to optical fiber installations, designing and measurements.
Entry requirements/
prerequisites
Course contents
1. Fiber Optic Transmission
2. Optical Fiber Characteristic
3. Fiber Optic Cables
4. Fiber Splicing
5. Optical Fiber Connectors
6. Optical Fiber Spliters and Couplers.
7. Budget Of Optical Fiber Line.
8. Fiber Optic Light Sources
9. Fiber Optic Detectors and Receivers
10. Cable Installation and Hardware.
11. Optical Time Domaind Reflectometry.
12. Optical Fiber Telecommunicaion Standards.
13. Optical Spectrum Measurements.
14. Chromatic and Polarization Dispersion Measurements
15. Fiber Optics Instalation Documentation.
Assessment methods Lecture, laboratory and numerical simulations
Learning outcomes
At successful completion of this course the students will be familiar with application of
optical fiber measurement methods to instalation problem solving, application of
instalation techniques, tools and resources, calculate the system bandwidth, budget Of
optical fiber line noise, probability of error and maximum usable bit rate of a telecom fibre
system.
Required readings 1. Govind P. Agrawal - Fiber-Optic Communication Systems Third Edition
2. Optical Fiber Communications by: G. Keiser; 3rd edition
30
Supplementary
readings
Additional information
Course title FUNDAMENTALS OF ENGINEERING ELECTROMEGNETICS
Field of study Electrical engineering
Teaching method Lectures with simple experiments, laboratory – computer simulations
Person responsible for
the course
Stanisław Gratkowski
(lab – Krzysztof Stawicki)
E-mail address to the
person responsible for
the course
Course code
(if applicable) ECTS points 3
Type of course Obligatory Level of course Bachelor
Semester Winter or summer Language of instruction English
Hours per week 2L/2Lab, other
organization is possible Hours per semester 30L/30Lab
Objectives of the
course
Students will learn mathematical and engineering principles that enable them to
understand forces, fields, and electromagnetic waves; know how devices work that use
those principles and phenomena; and be familiar with the historical context in which
development of knowledge and devices occurred.
Entry requirements/
prerequisites
Mathematics (a knowledge of vector calculus is helpful, but not necessary, since a short
introduction to vectors is provided); physics
Course contents
Electromagnetic field concept. Vector analysis. Electrostatics: Coulomb’s law, Gauss’s law
and applications, electric potential, electric dipole, materials in an electric field, energy and
forces, boundary conditions, capacitances and capacitors, Poisson’s and Laplace’s
equations, method of images. Steady electric currents: current density, equation of
continuity, relaxation time, power dissipation and Joule’s law, boundary conditions. Static
magnetic fields: vector magnetic potential, the Biot-Savart law and applications, magnetic
dipole, magnetic materials, boundary conditions, inductances, magnetic energy, forces and
torques. Time-varying electromagnetic fields: Faraday’s law, Maxwell’s equations, time-
harmonic fields, Poynting’s theorem, applications of electromagnetic fields. Plane wave
propagation: plane waves in lossless media, plane waves in lossy media, polarization of
wave. Computer aided analysis of electromagnetic fields.
Assessment methods Lectures – written and oral exam; laboratory – continuous assessment
31
Learning outcomes
On successful completion of this course:
Students will be familiar with the different vector operators used in Maxwells’ equations
Students will be able to describe and understand the basic concepts underpinning
electricity and magnetism such as potential and field
Students will have an understanding of Maxwell’s equations
Students will be able to select the most appropriate laws/theorems/ solution techniques for
electromagnetic field analysis
Required readings
1. Cheng D. K.: Fundamentals of Engineering Electromagnetics. Addison-Wesley
Publishing Company, Inc., New York 1993
2. Pollack G. L., Stump D. R.: Electromagnetism. Addison Wesley Publishing Company, Inc.,
New York 2002
3. Stewart J. V.: Intermediate Electromagnetic Theory. World Scientific Publishing Co. Pte.
Ltd., London 2001
4. Chari M. V. K., Salon S. J.: Numerical Methods in Electromagnetism. Academic Press, San
Diego 2000
Supplementary
readings
Additional information
Course title FUNDAMENTALS OF WEB DEVELOPMENT
Field of study ICT
Teaching method Lecture + project
Person responsible for
the course Przemyslaw Włodarski
E-mail address to the
person responsible for
the course
Course code
(if applicable) ECTS points 5
Type of course Optional Level of course Bachelor
Semester Winter or summer Language of instruction English
Hours per week 2 lect. / 2 proj. Hours per semester 30 lect. / 30 proj.
Objectives of the course This course is intended to present a set of technologies that enable creation of the fully
functional web page, working seamlessly on mobile, tablet and large screen browsers.
Entry requirements/
prerequisites Some programming experience (helpful but not necessary)
Course contents
Web page design blocks: HTML5 and CSS3 (syntax, images, hyperlinks, tables, multimedia,
etc.). Box model, positioning. Essential components of JavaScript (variables, arrays, loops,
functions) as well as JQuery (chaining, DOM elements, ajax, plugins). Server-side scripting
languages (PHP, Python): dynamic content, form processing, file handling, objects. Design
and implementation of database for web projects using MySQL (keys, data types, privileges
system). Interacting with file system, generating images, session control, user authentication
and personalization, responsive design.
32
Assessment methods Written exam (test), project work
Learning outcomes Knowledge of web development basics, including front-end as well as back-end side. Ability
to create web pages from scratch.
Required readings
1. Welling L., Thomson. L.: PHP and MySQL Web Development, 4th Edition, 2009.
2. Duckett J.: JavaScript and JQuery: Interactive Front-End Web Development, 1st Edition,
2014.
Supplementary
readings
1. Ducket J.: Web Design with HTML, CSS, JavaScript and jQuery Set 1st Edition, 2014.
2. Flanagan D.: JavaScript: The Definitive Guide: Activate Your Web Pages, 2011.
Additional information
Course title HIGH VOLTAGE ENGINEERING
Field of study High Voltage Engineering, Electrical Engineering
Teaching method lecture / laboratory
Person responsible for
the course Szymon Banaszak
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course Compulsory
Level of course bachelor
Semester winter or summer Language of instruction English
Hours per week 2 Lecture / 2 Lab Hours per semester 30 Lecture / 30Lab
Objectives of the
course
The aim of the subject is to acquaint students with high voltage technology, especially with
phenomena related to high voltages, construction of insulation systems, methods of
preventing or generating discharges, lightning and surge protection.
Entry requirements/
prerequisites
It is necessary to have basic information in the field of physics, electrical engineering,
material engineering.
Course contents
The course is based on the following points:
- economic issues of high voltage application,
- electric fields in various electrodes setups,
- practical applications of high voltage,
- dielectric strength and discharge development mechanisms in
vacuum/gas/liquids/solids,
- electric discharges, lightnings and protection against them,
- high voltage metrology and testing.
Assessment methods - written and oral exam (lecture),
- grade (laboratory)
33
Learning outcomes
Student gains knowledge on high voltage engineering including economic issues of high
voltage application, practical applications of high voltage and high voltage metrology and
testing.
Student is able to use methods and devices for measurement of high voltages, for proper
operation and development of high voltage insulation systems, knows safety precautions in
high voltage engineering.
Required readings E. Kuffel, W. S. Zaengl, J. Kuffel: High voltage engineering: fundamentals, Newnes (An
imprint of Elsevier), 2004
Supplementary
readings
1. M.S. Naidu, V. Kamaraju: High Voltage Engineering, Tata McGraw-Hill, 2009
2. H.M. Ryan: High Voltage Engineering and Testing, 2nd edition, The Institution of Electrical
Engineers, 2001
Additional information
Course title INDUSTRIAL ELECTRONICS PHD RESEARCH LAB
Field of study Electrical engineering, automatic control systems, industrial electronics, mechatronics,
robotics
Teaching method Lab work / classes
Person responsible for
the course Marcin Hołub
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 10
Type of course Obligatory Level of course doctoral
Semester winter or summer Language of instruction English
Hours per week 8 (6 Lab, 2 Classes) Hours per semester 120 (90 Lab, 30 Classes)
Objectives of the
course
To provide knowledge on research methodology, design methods and techniques, project
management, and to develop various skills useful in solving complex problems in the field
of power electronics, drive systems, embedded controller design.
Entry requirements/
prerequisites
Electrical engineering, basics of power electronics, basics of automatic control, drive
systems, microcontroller technology
Course contents
Individual research work on topics concerning interdisciplinary engineering and scientific
problems of the thesis. The specific topics are specified by the students at the beginning of
the semester, during consultation meetings; the topics may be also proposed by the
students. Research work is performed using Chair of Electrical Engineering and Drives
infrastructure, including labs, equipment, computers & software, Internet access, library,
copying facilities etc. Tutorials with supervisor – person involved in running all the project
topics – are carried out regularly during the whole semester, with presentation of the
progress in research work in the mid of semester, in a form of
a seminar open for all students and teachers. Final assessment of the project work is made
on the basis of evaluation of the progress by the supervisor and of oral presentation during
the second, final seminar (also open for all interested persons). Topics of research are to be
related to:
34
Power electronics simulation, design and construction
Industrial electronics
Drive control systems and algorithms
CAD design of power electronic prototypes
Prototype construction and testing
Embedded control systems for power electronics and industrial control
Complex analysis of industrial systems
Assessment methods Continuous assessment of lab and project work, evaluation of the oral presentation of the
project results during the final seminar
Learning outcomes
The student has knowledge on research and design methodology, and on performing
project work. He has practical skills useful in solving interdisciplinary problems in the field of
electrical engineering and industrial electronics.
Required readings
1. M. H. Rashid Power Electronics Handbook, Elsevier 2007, ISBN-13: 978-0-12-088479-7
2. Bimal Bose Power electronics and motor drives, Elsevier 2006, ISBN-13 978-0-12-
088405-6
3. K. Billings, T. Morey Switching power supply design, ISBN 978-0-07-148272-
1McGrawHill 2009
4. K. Billings Switchmode power supply handbook, ISBN 0-07-006719-8McGrawHill
1999
Supplementary
readings
Additional information
Course title INTRODUCTION TO CONTROL ENGINEERING
Field of Study
Automatic control and robotics; Electronics and telecommunication;
Information and communications technology;
Electrical engineering.
Teaching method Lectures, demonstrations, laboratory exercises
Person responsible for
the course Paweł Dworak
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course optional Level of course bachelor
Semester Winter or summer Language of instruction English
Hours per week 1L, 2Lab Hours per semester 15L, 30Lab
Objectives of the
course Ability of the analysis and design techniques of control systems.
Entry requirements
/prerequisites Basics knowledge of physics, mathematics and signal processing
Course contents Control history and state of the art. Classification of control systems. Principles of automatic
35
control. Closed loop systems. Feedback systems. Transfer function approach Determination
of transfer functions for simple systems. Characteristics of basic elements and elementary
systems. Frequency response representation – frequency domain specifications. Steady
state response – steady state error- static & dynamic error coefficients. Stability of linear
systems. Introduction to design – compensation techniques – P, PI, PD and PID control. Gain
scheduling, fuzzy logic, neural networks in control engineering.
All problems are validated with the use of the Matlab-Simulink.
Assessment methods Continuous assessment, laboratory reports.
Learning outcomes Students will be able to analyze a simple process and design the control loops.
Required readings Any book on control system design, feedback systems, linear control systems. Some
examples are listed as supplementary readings.
Supplementary
readings
1. Aström K.J.: Control System Design, 2002.
http://www.cds.caltech.edu/~murray/courses/cds101/fa02/caltech/astrom.html
2. Aström K.J., Murray R.M.: Feedback Systems: An Introduction for Scientists and
Engineers. http://www.cds.caltech.edu/~murray/amwiki/index.php/Main_Page
3. Coughanowr D.R.: Process systems analysis and control. McGraw-Hill, Inc., 1991.
4. Dorf R.C., Bishop R.H.: Modern Control Systems, Prentice Hall, 2001.
5. Doyle J., Francis B., Tannenbaum A.: Feedback Control Theory. Macmillan Publishing
Co., 1990.
6. Goodwin G., Graebe S.F., Salgado M.E.: Control System Design,. Prentice Hall, 2001.
7. Powell F., Naeini E.: Feedback Control of Dynamic Systems. Prentice Hall, 2002.
8. Rowland J.R.: Linear Control Systems. Modelling, analysis, and design. John Wiley,
New York, 1986 .
9. de Silva C.W.: Modeling and control of engineering systems. CRC Press, New Jersey,
2009.
Additional information
Course title INTRODUCTION TO CRYPTOGRAPHY
Field of study ICT
Teaching method lecture, written homework, labs
Person responsible for
the course Maciej Rafał Burak
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 3
Type of course optional Level of course bachelor
Semester winter or summer Language of instruction English
Hours per week 1 lecture / 2 lab Hours per semester 15 lecture / 30 lab
Objectives of the
course
This course explains the workings of basic cryptographic primitives and how to use them in
real world applications.
36
Entry requirements/
prerequisites
The course is self contained, however basic knowledge of probability theory will be helpful.
In order to complete the labs, basic programming knowledge is required (preferably in the
C language).
Course contents
Overview and history of cryptography. Vigenere (XOR) and Vernam (OTP) ciphers. Perfect
security. Block ciphers, modes of operations, semantic security. Stream ciphers.
Cryptographic hash functions, passwords and their weaknesses, brute force dictionary
attacks, salt. Data integrity, authenticated encryption. Key management and distribution.
Public key systems, certificates. SSL/TLS.
Assessment methods final (written) test, written homework, lab protocols
Learning outcomes Students will learn how to choose and apply cryptographic techniques to real-world
applications.
Required readings
Supplementary
readings
1. Menezes, van Oorschot and Vanstone. The Handbook of Applied Cryptography
2. Dan Boneh, Victor Shouph. A Graduate Course in Applied Cryptography
3. William, Stallings. Cryptography and Network Security
4. Ross Anderson. Security Engineering
Additional information
Course title INTRODUCTION TO ELECTRIC CIRCUITS 1
Field of study Electrical engineering
Teaching method Lecture, practical exercises and experimental laboratory
Person responsible for
the course
Tomasz Chady
Przemysław Łopato
Grzegorz Psuj
Krzysztof Stawicki
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course Obligatory Level of course Bachelor
Semester winter or summer Language of instruction English
Hours per week 2L / 1Practical / 2Lab Hours per semester 30L / 15Practical /
30Lab
Objectives of the
course
To teach students basics of electrical circuit theory
To give students an understanding of the laws governing the behavior of electrical
circuits, and the ability to apply this understanding to the direct current and sinusoidal
steady-state circuit analysis
To give students an understanding of the analysis and design of common circuits
Entry requirements/
prerequisites Academic course of mathematics and physics
37
Course contents
Introduction and electric circuit variables (Definitions, Units, Types of signals, Circuits
and current flow, units, voltage, power and energy)
Circuit elements (linear model, active and passive elements, independent and
dependent elements)
Resistive circuits (resistors, Ohm and Kirchhoff’s law, basic circuit analysis)
Circuit theorems (superposition, substitution, fitting, Thevenin’s and Norton’s theorem)
Circuit analysis (nodal analysis, mesh analysis )
Energy storage elements (inductors, capacitors)
Sinusoidal steady-state analysis (classical method, phasor method, circuit law in phasor
method)
Ideal and real resonance, frequency characteristics
Laboratory experiments for selected topics.
Assessment methods Written exam (Lect.) + Continuous assessment (Practical, Lab)
Learning outcomes
Upon successful completion of the course, the student will be able to:
think analytically and creatively to draw conclusions and solve problems,
apply Ohm's and Kirchhoff's laws to solve for unknown voltage and/or currents
simplify series and parallel combinations of passive and active elements
use nodal analysis to write simultaneous equations
use mesh analysis to write simultaneous equations
apply superposition to linear circuits analysis
use Thevenin / Norton equivalent circuits to analyze circuits linear and selected
nonlinear circuits
analyze steady state sinusoidal circuits using the advanced circuit analysis techniques
(phasor method)
use phasor diagrams to visualize responses of the circuits
analyze RLC circuits in case of resonance
use basic instruments to measure voltages and currents
identify and apply the most appropriate circuit analysis technique
Required readings 1. W.H. Hayt, J.E. Kemmerly: Engineering circuit analysis, McGraw-Hill Book Company,
ISBN 0-07-027393-6
Supplementary
readings
1. Charles K. Alexander and Matthew N.O. Sadiku: Fundamentals of Electric Circuits, 2nd
Edition, , 4th Edition, McGraw-Hill, 2009
2. J.O. Attia: Pspice and Matlab for Electronics, CRC Press 2002, ISBN 0-8493-1263-9
Additional information Maximum number of students in case of the laboratory group: 12
Course title INTRODUCTION TO ELECTRIC CIRCUITS 2
Field of study Electrical engineering
Teaching method Lecture and experimental laboratory
Person responsible for
the course
Tomasz Chady
Przemysław Łopato
Grzegorz Psuj
Krzysztof Stawicki
E-mail address to the person
responsible for the course [email protected]
38
Course code
(if applicable) ECTS points 4
Type of course Obligatory Level of course Bachelor
Semester winter or summer Language of instruction English
Hours per week 3L / 2Lab Hours per semester 45L / 30Lab
Objectives of the
course
To give students an understanding of the laws governing the behavior of electrical
circuits, and the ability to apply this understanding to the advanced methods of circuit
analysis in a steady and transient state
To give students an understanding of the analysis and design of common circuits in a
steady and transient state
To teach students how to use computer simulators for circuits analysis
Entry requirements/
prerequisites
Academic course of mathematics and physics
Academic course: Introduction to electric circuits 1
Course contents
Three phase circuits (symmetric Y and triangular, unsymmetrical circuits, power, reactive
power compensation)
Self and mutual inductance (ideal and with ferromagnetic core transformers)
Transient phenomena (DC and AC circuits)
The Laplace transformation (direct and inverse transformation)
Analysis of complex circuits in the transient state
The amplifiers (the operational and ideal operational amplifier)
Two-port’s (passive, active, equations, T and Pi scheme, A, A-1 Y, Z, h, g parameters,
relationship between parameters, interconnection of two port networks)
Fourier series (formulas, spectrum, power, compensation reactive power)
Digital transformation (Nyquist’s formula, Shannon’s formula)
Filters ( passive, active and digital)
Computer simulators for circuit analysis (SPICE)
Laboratory experiments for selected topics.
Assessment methods Written exam (Lect.) + Continuous assessment (Lab)
Learning outcomes
Upon successful completion of the course, the student will be able to:
think analytically and creatively to draw conclusions and solve problems,
identify, formulate, and solve engineering problems
analyze steady state sinusoidal three phase circuits,
use phasor diagrams to visualize responses of the three phase circuits,
analyze transient state in the first and second order RLC circuits by solving the
differential equations and using the Laplace transform.
identify and apply the most appropriate circuit analysis technique,
know the characteristics of the opamp,
use opamps in order to achieve the desired function,
use Fourier series to analyze circuits with no sinusoidal sources,
use the two port networks,
design passive and active filters with desired characteristics,
use computer simulators (SPICE) for numerical circuit modelling and analysis,
critically evaluate their chosen problem solving techniques and the accuracy of their
answers.
Required readings 1. W.H. Hayt, J.E. Kemmerly: Engineering circuit analysis, McGraw-Hill Book Company,
ISBN 0-07-027393-6
39
Supplementary
readings
1. Charles K. Alexander and Matthew N.O. Sadiku: Fundamentals of Electric Circuits, 2nd
Edition, , 4th Edition, McGraw-Hill, 2009
2. J.O. Attia: Pspice and Matlab for Electronics, CRC Press 2002, ISBN 0-8493-1263-9
Additional information Maximum number of students in case of the laboratory group: 12
Course title INTRODUCTION TO MULTISENSOR DATA FUSION
Field of study Electrical engineering and computer engineering
Teaching method Lectures with simple cases presentations, project – design and implementation of data
fusion algorithm
Person responsible for
the course Grzegorz Psuj
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 2
Type of course obligatory Level of course bachelor/master
Semester Winter or summer Language of instruction English
Hours per week 1 L / 1 P Hours per semester 15 L/15 P
Objectives of the
course
This course is intended to present an introduction to the multisensor data fusion concept
and theory followed by the case study.
Entry requirements/
prerequisites
Academic course of mathematics and informatics. Basics of programming in
Matlab/Octave/SciLab or other similar environment.
Course contents
1. Introduction: motivation, concepts and theory of data fusion.
2. Data fusion models and architectures.
3. Sensors types.
4. Levels of data fusion.
5. Data registration: concepts and theory, algorithms partition and basic description,
examples.
6. Data fusion algorithms: concepts and theory, algorithms partition and basic
description.
7. Quality assessment factors of performance evaluation.
Case study of data fusion applications.
Assessment methods Lectures – exam; project – report assessment
Learning outcomes
Student knows:
the basic theory about the data fusion concept,
the rules of data fusion models, architectures and levels division,
the procedure of the data registration process,
the commonly used quality factors,
examples of most commonly used algorithms.
Student can design, adopt, proceed and assess the data fusion algorithm for exemplary
cases.
40
Required readings
1. D. L. Hall, Sonya A. H. McMullen: Mathematical Techniques in Multisensor Data Fusion,
Artech House Publishers, 2004
2. M. E. Liggins, D. L. Hall, James Llians: Handbook of Multisensor Data Fusion, CRC Press
LLC, 2nd ed., 2009
Supplementary
readings
1. L. A. Klein: Sensor and Data Fusion. A tool for Information assessment and Decision
Making., SPIE Press, 3rd ed., 2010
2. X. E. Gros: Application of NDT Data Fusion, Kluwer Academic Publishers, 2001
3. H.B. Mitchell, Multi-Sensor Data Fusion: An Introduction, Springer, 2007, ISBN
3540715592, 9783540715597
Additional information
Course title INTRODUCTION TO SOUND RECORDING TECHNOLOGY
Field of study Electronics and Telecommunications
Automatic Control and Robotics
Teaching method lectures, workshop, laboratory, project
Person responsible for
the course Witold Mickiewicz
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course optional Level of course Bachelor, master
Semester Winter or summer Language of instruction English
Hours per week 15 L / 2 Lab Hours per semester 15 L / 30 Lab
Objectives of the
course
To provide knowledge on selected topics on sound engineering, recording technology and
electroacoustical measurements.
Entry requirements/
prerequisites Basic knowledge in Physics
Course contents
Lectures: Objectives of sound engineering and recording technology. Basics of musical
sound descriptions. Sound sources properties. Two- and multichannel reproduction
systems. Electroacoustical transducers and electroacoustical systems. Microphone
technique. Analog and digital recording systems. DAW. Digidal audio signal processing.
Production of speech and music recordings. On location recording techniques. Mastering.
Labs: measurements of sound intensity, parameters of microphones and loudspeakers,
stereo recordings using AB, XY, MS and ORTF methods, mixing desk applications,
reverberation time measurement. Production of recordings sessions in studio and on
location, non-linear sound editing, mastering
Assessment methods Written exam, accomplishment of practical labs
Learning outcomes
Students will be able to explain the basic techniques of recording, processing and play back
audio signals. Also gain the skills in electroacoustic and sound recording system use, design
and measurements.
41
Required readings 1. Howard D. H.: Acoustics and psychoacoustics. Focal press, 2001.
2. Everest F. A.: Master handbook of acoustics. McGraw-Hill, 2001.
Supplementary
readings
1. Blauert J.: Spatial Hearing - Revised Edition: The Psychophysics of Human Sound
Localization. MIT Press, 1999.
Additional information
Course title M.Sc. Thesis
Teaching method Individual work with the thesis supervisor
Person responsible for
the course
Depends on the subject of the
thesis
E-mail address to the person
responsible for the course
Course code
(if applicable) ECTS points 20
Type of course Obligatory Level of course master
Semester Winter or summer Language of instruction English
Hours per week Hours per semester 15 hours
Objectives of the
course
This course is intended to help students with their M.Sc. thesis. The work is either a project
or a research. It can result in e.g. creating a computer program, laboratory work station, a
device-model or presenting results of research carried out using professional devices or
programs.
Entry requirements
- Knowledge of basic issues related to the subject of the thesis
- Ability to formulate technical texts and prepare drawings and diagrams presenting
gained results
Course contents
Doing a M.Sc. thesis is in fact realization of a complex engineering task containing scientific
elements, that starts with formulating a problem and making assumptions, analyzing
current state of the art and defining the scientifically justifiable method of realizing the aim
of the work. At the end of the task, the student formulates conclusions and prepares written
description of performing the task, its results and analysis.
Assessment methods Continuous assessment and instructions given by the supervisor
Learning outcomes
Knowledge of modern solutions and the scientific achievements related to the subject of
the thesis, ability to write detailed technical reports and prepare related multimedia
presentations, ability to find the necessary information in the scientific literature and
technical documentation
Recommended
readings Depends on the subject of the thesis
Additional information Please contact the faculty Erasmus coordinator to discuss the details of the course.
42
Course title MACHINE LEARNING
Field of study ICT
Teaching method Lecture + project
Person responsible for
the course Adam Krzyzak
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 6
Type of course optional Level of course bachelor
Semester summer Language of instruction English
Hours per week 2 Lecture / 2 project Hours per semester 30 Lecture / 30 project
Objectives of the
course
This course is intended to present a unified approach to machine learning techniques and
algorithms and their applications in practical problems
Entry requirements/
prerequisites
Basic knowledge of Matlab or Mathcad environments,
basic knowledge about programming
basic knowledge of linear algebra, probability and statistics
Course contents
Classification. Generative vs. discriminative learning. Naive Bayes. Gaussian discriminant
analysis. Linear models: linear and polynomial regression, overfitting, model selection, L2
and L1 regularization, sparse models, logistic regression. Non-linear models: decision trees,
instance-based learning, boosting, neural networks. Support vector machines and kernels.
Computational learning theory. Unsupervised learning: clustering, K-means, mixture models,
density estimation, expectation maximization. Autoencoder, PCA, eigenmaps and other
dimensionality reduction methods. Structured models: graphical models, Bayes nets.
Learning in dynamical systems: Hidden Markov Models and other types of
temporal/sequence models. Approximate inference. Gibbs sampling. Deep belief learning.
Assessment methods Written exam (test) / project work
Learning outcomes Knowledge of basic machine learning algorithms. Ability to implement some machine
learning algorithms in chosen environment (e.g. Matlab).
Required readings 1. Christopher M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006.
Supplementary
readings
1. Trevor Hastie, Robert Tibshirani and Jerome Friedman, The Elements of Statistical
Learning, Second Edition, Springer, 2009.
2. Garreth James, Daniela Witten, Trevor Hastie and Robert Tibshirani, An Introduction to
Statistical Learning, Springer, 2013.
3. Ethem Alpaydin, Introduction to Machine Learning, Second Edition, MIT Press, 2009.
4. Tom Mitchell, Machine Learning, McGraw-Hill, 1997
Additional information
43
Course title MANAGING MODEL-BASED DEVELOPMENT
Field of study Control Engineering, ICT
Teaching method Lectures, simple examples; Lab – software tools learning with examples; Project – computer
modeling
Person responsible for
the course Krzysztof Pietrusewicz
E-mail address to the
person responsible for
the course
Course code
(if applicable) ECTS points 3
Type of course Obligatory Level of course Bachelor/Master
Semester Winter or summer Language of instruction English
Hours per week 1 Lecture, 1 Lab, 1 Project Hours per semester 15 Lecture, 15 Lab, 15 Project
Objectives of the
course
This course is intended to present basics of managing model-based design and
development with the use of modern software tools. Additional goal is to present possible
workflows of implementation of model-based design procedures in industry.
Entry requirements/
prerequisites
Mechatronics, Control theory, Computer science, Requirements management in research
projects on complex systems, Modeling of complex systems with the use of SysML
Course contents
1. Phases of model-based design, understanding purposes of V-model 2. Graphical
specifications 3. Code generation possibilities 4. Simulation possibilities 5. Hardware in the
loop: when and how? Science or industry? 6. Virtual verification and validation 7. Workflows
for effective implementation of model-based design
Assessment methods Lectures – project public presentation during seminar, Lab – validation on preparation level,
Project – continuous assessment
Learning outcomes
After this course student is able to:
1. understand the need for managing system models
2. have knowledge about modern software and hardware tools used for industry oriented
model-based design
3. see the need of create clear connections between production code of control system with
its graphical specifications
4. conduct virtual verification and validation procedures within mechatronic projects
5. understand obstacles on the road of effective implementation of model-based design in
industry
Required readings
1. Holt J., Perry S.A., Brownsword M., Model-based requirements engineering, 2012, ISBN
978-1-84919-487-7
2. ISO/IEC/IEEE 29148:2011, Systems and software engineering - Life cycle processes -
Requirements engineering. 2011
3. Friedenthal S., Moore A., Steiner R., A practical guide to SysML. The systems modeling
language, 2015, ISBN 978-0-12-800202-5
4. Delligatti L., SysML distilled, A Brief Guide to the Systems Modeling Language, 2014, ISBN
978-0-321-92786-6
5. Aarenstrup R., Managing model-based design, 2015, ISBN-13: 978-1512036138
44
Supplementary
readings
1. The Official OMG SysML website, http://www.omgsysml.org/
2. Papyrus UML for Eclipse website, https://eclipse.org/papyrus/
3. Visual Paradigm website, http://www.visual-paradigm.com/
4. Sparx Enterprise Architect website, http://www.sparxsystems.com.au/
5. Mathworks official website, http://www.mathworks.com/
Additional information
Course title MEDICAL IMAGING SYSTEMS
Field of study Image Processing
Teaching method lectures, labs
Person responsible for
the course Piotr Okoniewski
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 3
Type of course compulsory Level of course master
Semester Winter or summer Language of instruction English
Hours per week 2 L / 1 Lab Hours per semester 30 L / 15 Lab
Objectives of the
course
To provide up to date knowledge on various modalities of biomedical imaging technologies
and algorithms to develop practical skills useful in this area.
Entry requirements/
prerequisites Mathematics, Informatics, Signal processing, Image processing, Biomedical Engineering
Course contents
Lectures: Medical imaging systems – physical principles of image formation and equipment
in Thermography (TG), Ultrasonography (USG), Nuclear Medicine (Gamma-camera, SPECT,
PET), Digital Radiography (DR), Computed Tomography (CT), Magnetic Resonance Imaging
(MRI). Special techniques, e.g. ultra-fast data acquisition systems in MRI (EPI), Functional
and Interventional MRI. Principles of image reconstruction (2-D, 3-D). Image processing,
analysis and measurement; software tools. Image fusion. Image transmission and archiving
– PACS, standard DICOM 3. DICOM validation tools
Labs: Image browsing & analysis tools: systems OSIRIS/PAPYRUS and PC-Image. DICOM
validation tools. MATLAB and LabView systems in image processing.
Assessment methods Lectures: grade, accomplishment of lab tasks
Learning outcomes
The student has increased knowledge on methods and techniques used in medical
diagnostic imaging, systems and archiving/communication standards as well as on research
methodology used in this field. He has practical skills useful in this area regarding
biomedical imaging systems testing, development, and exploitation
45
Required readings
1. Bronzino J. D. (ed.): “Biomedical Engineering Handbook”. CRC Press, IEEE Press, 1995
2. Robb R. A.: “Three Dimensional Biomedical Imaging: Principles and Practice”. Wiley-Liss,
N.Y., 1998
3. Shellock F. G., Kanal E.: “Magnetic Resonance. Bioeffects, Safety and Patient
Management”. Raven Press, N.Y., 1994
Supplementary
readings
1. Huang H. K.: “PACS in Biomedical Imaging”. VCH Publ. Inc., N.Y., 1996
2. IT-EDUCTRA. FUNDESCO, Commission of the EC, 1998
Additional information
Course title MODELING OF COMPLEX SYSTEMS WITH THE USE OF SYSML
Field of study Control Engineering, ICT
Teaching method Lectures, simple examples; Lab – software tools learning with examples; Project – computer
modeling
Person responsible for
the course Krzysztof Pietrusewicz
E-mail address to the
person responsible for the
course
Course code
(if applicable) ECTS points 3
Type of course Obligatory Level of course Bachelor/Master
Semester Winter or summer Language of instruction English
Hours per week 1 Lecture, 1 Lab, 1
Project Hours per semester 15 Lecture, 15 Lab, 15 Project
Objectives of the
course
This course is intended to present basics of complex system modeling, software tools and
methods for effective representation of complex systems with the use of graphical
specifications, that can be used for control software code generation purposes.
Entry requirements/
prerequisites
Mechatronics, Control theory, Computer science, Requirements management in research
projects on complex systems
Course contents
1. Modeling complex systems – where is a need for that? 2. Breakdown of complex systems
into simple functional units 3. How to combine requirements with implementation
(structure and behavior of system components) and testing (unit, interface, integration)
4. SysML graph types 5. Example of complex system modeling from automotive industry
6. Example of complex system modeling from machine tool industry
Assessment methods Lectures – project public presentation during seminar, Lab – validation on preparation level,
Project – continuous assessment
Learning outcomes
After this course student is able to:
1. understand the need for modeling systems
2. create selected SysML graphs for complex systems modeling
3. create interactions between different SysML models and combine them within integrated
system model
4. create documentation for the modelled/designed system
46
Required readings
1. Holt J., Perry S.A., Brownsword M., Model-based requirements engineering, 2012, ISBN
978-1-84919-487-7
2. ISO/IEC/IEEE 29148:2011, Systems and software engineering - Life cycle processes -
Requirements engineering. 2011
3. Friedenthal S., Moore A., Steiner R., A practical guide to SysML. The systems modeling
language, 2015, ISBN 978-0-12-800202-5
4. Delligatti L., SysML distilled, A Brief Guide to the Systems Modeling Language, 2014, ISBN
978-0-321-92786-6
Supplementary
readings
1. The Official OMG SysML website, http://www.omgsysml.org/
2. Papyrus UML for Eclipse website, https://eclipse.org/papyrus/
3. Visual Paradigm website, http://www.visual-paradigm.com/
4. Sparx Enterprise Architect website, http://www.sparxsystems.com.au/
5. Mathworks official website, http://www.mathworks.com/
Additional information
Course title MODERN ELECTRICAL MACHINES
Field of study Electrical engineering
Teaching method Lecture, Project
Person responsible for
the course Ryszard Pałka
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 6
Type of course Obligatory or optional Level of course master
Semester winter or summer Language of instruction English
Hours per week 2L / 1P Hours per semester 30L, 15P
Objectives of the
course
The course gives the fundamental and expert knowledge about construction, development,
numerical evaluation and optimization of modern electrical machines.
Entry requirements/
prerequisites
Basics of electrical engineering, basics of electrical machines, electromagnetic field theory,
numerical methods.
Course contents
The course gives the knowledge about construction of modern electrical machines:
Permanent magnet excited synchronous machines,
Transverse flux machines, axial flux machines,
Switched reluctance machines,
Different electrical machines for hybrid and pure electric vehicles.
Assessment methods Written exam, project work
Learning outcomes
47
Required readings
1. Gieras J. F., Wing M.: Permanent magnet motor technology. Wiley&Sons 2008
2. Austin Hughes; Electric Motors and Drives. Elsevier Ltd. 2006
3. Chiasson J.: Modeling and high-performance control of electric machines. Wiley&Sons
2005
4. Larminie J., Lowry J.: Electric Vehicle Technology Explained. Wiley&Sons 2003
Supplementary
readings
1. Gieras J. F., et al.: Noise of Polyphase Electric Motors. CRC Press 2006
2. Pyrhoenen J., et al.: Design of Rotating Electrical Machines, Wiley & Sons, 2008
Additional information
Course title MULTISTRUCTURED OPTICAL FIBRES APPLICATIONS
Field of study
Electronics and Telecommunications ,
Automatic Control and Robotics,
Electrical Engineering ,
Teleinformatics
Teaching method Lecture + project
Person responsible for
the course
Prof. Ewa Weinert-Raczka
Dr Grzegorz Zeglinski
E-mail address to the
person responsible for the
course
Course code
(if applicable)
ECTS points 2
Type of course facultative Level of course master
Semester winter Language of instruction English
Hours per week 1h-lecture, 1h-project Hours per semester 15h—lecture
15h-project
Objectives of the
course
The first objective of this course is to give basic
concepts relating to special optical fiber
Entry requirements/
prerequisites
Course contents
1. Introduction to optical fiber theory.
2. Fabrication of fibres
3. Modes of Optical Fibers. Single Mode and Multimode Fibres.
4. Chromatic Dispersion.
5. Polarization Mode Dispersion.
6. Holey and Photonic Crystal Fibres. Photonic Bandgap Guidance.
7. SuperContinnuum Generation.
8. Optical Fibres for sensors
9. Fiber Bragg Gratings
10. Multicore Fibres
11. Polymer Optical Fibres
12. Optical Fibers Interferomers
13. Modelling and Design of Microstructured Fibres
14. Application of Special Optical Fibres
48
Assessment methods project work
Learning outcomes
At successful completion of this course the students will be familiar with special optical
fibers - propagation, modelling and design. The
course will also provide the basic knowledge of
methods of propagation modeling in Microstructured Opticial Fibres and applications of
special optical fibres
Required readings
1] Argyros A.: Microstructures in Polymer Fibres for Optical Fibres, THz Waveguides, and
Fibre-Based Metamaterials, Institute of Photonics and Optical Science, School of Physics,
The University of Sydney, Sydney, NSW 2006, Australia
[2] Ziemann O., Krauser J., Zamzow P.E., Daum W.: POF Handbook, Optical Short Range
Transmission Systems. Springer-Verlag, 2008.
Supplementary
readings
Additional information
Course title NETWORK SYSTEMS ADMINISTRATION
Field of study ICT
Teaching method Lecture / laboratory
Person responsible for
the course Piotr Lech
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course obligatory Level of course bachelor
Semester summer Language of instruction English
Hours per week 1 Lecture / 2 Lab. Hours per semester 15 Lecture/
30 Laboratory
Objectives of the
course
The course introduces students to the fundamentals of network management, primarily for
TCP/IP networks. Students are introduced to networking protocols, hardware, architecture,
media, and software and experience hands-on management of typical network
components.
Entry requirements/
prerequisites Prerequisites and additional requirements not specified
Course contents
Determine the network design most appropriate for a given site. Installation and
configuration of network services. Differentiate among network standards, protocols, and
access methods. Master local area network concepts and terminology. Network planning,
network equipment (hub, switch, router). Protocols TCP/IP, IP nets, IP subnets, VLAN .
Protocol analysis. Network administration (SNMP, RMON)
Assessment methods Written exam (test), continuous assessment (laboratory)
49
Learning outcomes
Working knowledge of networking terms and concepts pertaining to system administration,
terms that characterize the attributes of networks and aspects of network operation. Ability
to observation of system behavior. Ability actions taken to accomplish sysadmin related to
administration tasks.
Required readings
1. Tony Bautts, Terry Dawson, Gregor N. Purdy Linux Network Administrator's Guide, 3rd
Edition O'Reilly Media 2005 ISBN: 978-0-59600-548-1 AEleen Frisch Essential System
Administration, 3rd Edition O'Reilly Media 2002 ISBN:978-0-59600-343-2 Sander van
Vugt Pro Ubuntu Server Administration Apress 2008 ISBN: 978-1-4302- 1622-3
Supplementary
readings Selected RFC documents.
Additional information
Course title NETWORK TRAFFIC
Field of study ICT
Teaching method Lecture + laboratory
Person responsible for
the course Przemyslaw Włodarski
E-mail address to the
person responsible for
the course
Course code
(if applicable) ECTS points 5
Type of course Optional Level of course Bachelor
Semester Winter or summer Language of instruction English
Hours per week 1 lect. / 2 lab. Hours per semester 15 lect. / 30 lab.
Objectives of the course This course is intended to present selected issues of ICT network traffic and performance
evaluation.
Entry requirements/
prerequisites Fundamentals of computer networks.
Course contents
Configuration and performance evaluation for different network setups (bandwidth, buffer
size, transport layer protocols). Capturing, filtering and inspecting of L2 and L3 layers. Delay
and loss analysis. Network traffic generation model. Synthesis of traffic flows based on
stochastic processes. Collecting data using SNMP. Traffic shaping and control using
classless (SFQ, GRED, TBF) and classful (HTB, CBQ, PRIO) queueing disciplines. Basic queues
and their impact on network traffic. Configuration of multicast and real-time applications
(IGMP, RSVP, RTP).
Assessment methods Written exam (test), assessment and reports (lab.)
50
Learning outcomes Knowledge of network traffic issues and performance evaluation. Ability to configure and
control network traffic in various applications (best effort, real-time).
Required readings 1. Armitage G.: Quality of Service in IP Networks: Foundations for a Multi-service Internet,
2000.
Supplementary
readings
1. Welzl M.: Network Congestion Control: Managing Internet Traffic, 2005.
2. Ash G. R.: Traffic Engineering and QoS Optimization of Integrated Voice and Data
Networks, 2006.
Additional information
Course title NON-DESTRUCTIVE TESTING (NDT) USING RADIOGRAPHIC (X-RAY) AND
TERAHERTZ METHOD
Field of study Electrical engineering, Mechanical engineering
Teaching method Lecture and laboratory experiments
Person responsible for
the course Tomasz Chady
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course Obligatory
Level of course Bachelor, Master
Semester winter or summer Language of instruction English
Hours per week 1L / 1Lab Hours per semester 15L / 15Lab
Objectives of the
course
To give basic knowledge of techniques for non-destructive testing (NDT),
To teach how to apply Xray and THz method in practical applications,
To introduce modern systems and techniques for NDT
Entry requirements/
prerequisites Academic course of mathematics and physics (required)
Course contents
Non-destructive testing - the introduction, the basic idea, the historical background
Review of different methods of non-destructive testing
Radiation Sources
Computer radiography using imaging plates
Digital radiography
Evaluation of low conductivity materials using electromagnetic waves of high frequency
(THz – terahertz TDS imaging)
Simulators of NDT systems,
The algorithms of digital signal processing in NDT
Industrial tomography
Special Radiographic Techniques
Laboratory experiments for selected topics.
51
Assessment methods Continuous assessment (Lect.) + Continuous assessment (Lab)
Learning outcomes
Upon successful completion of the course, the student will be able to:
identify, formulate, and solve engineering problems in the field of NDT,
explain the principles of the major NDT methods,
identify advantages and limitations of nondestructive testing methods and to select the
appropriate techniques for inspections in specific application,
use selected software for numerical modelling of NDT systems,
use selected hardware for practical NDT (i.e. THz TDS or digital detectors and IP scanner
for X-ray testing).
Required readings 1. Hellier C. J., Handbook of Nondestructive Evaluation, McGrown-Hill, 2003
2. Sakai K., Terahertz Optoelectronics, Springer-Verlag Berlin Heidelberg 2005
Supplementary
readings
1. Nondestructive Testing Handbook, Third Edition: Volume 4, Radiographic Testing (RT),
ASNT, 2005.
Additional information Maximum number of students in case of the laboratory group: 8
Course title NONLINEAR CONTROL
Field of study Automatic Control and Robotics
Teaching method Lectures covering basic modelling of nonlinear systems, dynamics, control methods.
Laboratory course covering various applications and control design.
Person responsible for
the course Adam Łukomski
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 3
Type of course optional Level of course bachelor
Semester Winter / summer Language of instruction english
Hours per week 1h lecture, 2h laboratory Hours per semester 15h lecture,
30h laboratory
Objectives of the
course The Student will learn to design and apply nonlinear control methods.
Entry requirements/
prerequisites Linear control, Dynamical systems, Mathematics, Physics
Course contents
This course covers modelling of nonlinear systems using Newton-Euler and Euler-Lagrange
methods, stability analysis using Lyapunov functions, passive systems, phase-plane
portraits, feedback linearisation, partial feedback linearisation for underactuated systems
and control analysis. The laboratory course covers modelling and control of basic nonlinear
systems, using both simulation and laboratory equipment (inverted pendulum on a cart,
motor positioning, simple robotic manipulator).
52
Assessment methods Written exam (on last lecture), Continuous assessment during laboratory course
Learning outcomes Ability to model, analyse and control a nonlinear system.
Required readings 1. Slotine, Jean-Jacques E., and Weiping Li. Applied nonlinear control. Prentice-hall, 1991.
Supplementary
readings
1. Khalil, Hassan K. Nonlinear systems. Prentice Hall, 1996
2. Featherstone, Roy. Rigid body dynamics algorithms. Springer, 2008.
3. Isidori, Alberto. Nonlinear control systems. Springer, 1995.
Additional information
Course title OBJECT-ORIENTED PROGRAMMING IN C#
Field of study Electrical Engineering, Computer Engineering, Electronic Engineering, Information
Technology Engineering
Teaching method Lectures, Laboratory
Person responsible for
the course Marcin Ziółkowski
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course Obligatory Level of course Bachelor, Master
Semester Winter or summer Language of instruction English
Hours per week Lectures - 2
Laboratory - 2 Hours per semester
Lectures - 30
Laboratory – 30
Objectives of the
course
This course is intended to present object-oriented programming techniques in C#
language.
Entry requirements/
prerequisites Mathematics
Course contents
10. Application structure in C#
11. Data Types
12. Loops
13. Static Methods
14. Exceptions
15. Files and Streams
16. Arrays
17. Structures
18. Classes
19. Constructor
20. Inheritance
21. Abstract Classes
22. Polymorphism
53
23. Collections
24. Windows Forms
Assessment methods Lectures – written exam; Laboratory – continuous assessment
Learning outcomes Students will get the knowledge about modern object-oriented language.
Required readings
1. A. Hejlsberg, M. Torgersen, S. Wiltamuth, P. Gold: The C# Programming Language,
Addison-Wesley, 2011
2. D. Clark: Beginning C# Object-Oriented Programming, APress, 2011
3. M. McMillan: Data Structures and Algorithms using C#, Cambridge University Press,
2007
Supplementary
readings
Additional information
Course title OPTIMIZATION THEORY
Field of study Electrical Engineering, Computer Engineering, Electronic Engineering, Information
Technology Engineering, Automation and Robotics Engineering
Teaching method Lectures, Laboratory
Person responsible for
the course Marcin Ziółkowski
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course Obligatory Level of course Master
Semester Winter or summer Language of instruction English
Hours per week Lectures - 2
Laboratory - 2 Hours per semester
Lectures - 30
Laboratory – 30
Objectives of the
course
This course is intended to present a unified approach to various optimization methods
(advanced undergraduate level).
Entry requirements/
prerequisites Numerical Methods, Mathematics, Physics
Course contents
1. One-Dimensional Search Methods (Golden Section Search, Fibonacci Search, Newton's
Method, Secant Method)
2. Gradient Methods
3. Genetic Algorithms
4. Simplex Methods, Non-Simplex Methods
5. Single Objective Optimization and Multi Objective Optimization Problems
6. Discrete Ill-Posed Problems
7. Direct Regularization Methods
8. Iterative Regularization Methods
54
9. Methods for Choosing the Regularization Parameter
10. A Discrete L-Curve for the Regularization of Ill-Posed Inverse Problems
11. Single Objective Optimization of an Exciter for Magnetic Induction Tomography
12. Multi Objective Optimization of an Exciter for Magnetic Induction Tomography
13. Magnetic Field Synthesis on a Solenoid's Axis (Solving Ax = b using Least-Squares
Analysis, Recursive Least-Squares Algorithm, Solution to Ax = b Minimizing ||x||)
14. Topology Optimization of a Magnetic Field in a Three-dimensional Finite Region
Assessment methods Lectures – written exam; Laboratory – continuous assessment
Learning outcomes Students will get the knowledge about various optimization methods. They will be able to
use an appropriate method to the given practical problem.
Required readings
1. Edwin K.P. Chong, Stanislaw H. Żak: An Introduction to Optimization, Second Edition,
Wiley & Sons, Inc, 2001, New York, USA
2. R. Fletcher: Practical Methods of Optimization, second Edition, Wiley, 2000
Supplementary
readings
1. Per Christian Hansen: Regularization Tools, Technical University of Denmark, Lyngby,
2008
Additional information
Course title PATTERN RECOGNITION AND CLASSIFICATION
Field of study ICT
Teaching method Lecture + project
Person responsible for
the course Adam Krzyzak
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course optional Level of course bachelor
Semester summer Language of instruction English
Hours per week 2 Lecture / 2 project Hours per semester 30 Lecture / 30 project
Objectives of the
course
This course is intended to present a unified approach to pattern recognition and
classification techniques and their applications in real life problems
Entry requirements/
prerequisites
Basic knowledge of Matlab or Mathcad environments,
basic knowledge about programming
basic knowledge of linear algebra, probability and statistics
55
Course contents
Introduction to the subject of pattern recognition. Bayesian decision theory, discriminant
functions for normal class distributions, parameter estimation and supervised learning,
nonparametric techniques (nearest neighbor rules, Parzen kernel rules, tree classifiers),
Adaboost, Breiman random forest, linear discriminant functions, Fisher linear discriminant
and learning including perceptron learning, LMS algorithms and support vector machines,
unsupervised learning and clustering, neural networks including multilayer perceptrons and
radial basis networks, and elements of machine learning. Feature selection and
dimensionality reduction including PCA, SOM and Laplacian maps. Applications of pattern
recognition in biometrics including handwriting recognition, face recognition and
fingerprint recognition.
Assessment methods Written exam (test) / project work
Learning outcomes Knowledge of basic pattern recognition algorithms. Ability to implement some pattern
recognition algorithms in chosen environment (e.g. Matlab).
Required readings 1. R. O. Duda, P. E. Hart and D. G. Stork, Pattern Classification, Wiley, Second Edition,
2001.
Supplementary
readings
1. Sergios Theodoridis and Konstantinos Koutroumbas, Pattern Recognition, Fourth
Edition, Academic Press, 2008.
2. Brian Ripley, Pattern Recognition and Neural Networks, Cambridge University Press,
2008.
3. Simon Haykin, Neural Networks and Learning Machines, Third Edition, Prentice Hall,
2008.
4. Nello Cristianini and John Shawe-Taylor, An Introduction to Support Vector Machines
and other Kernel-Based Learning Methods, Cambridge University Press, 2000.
Additional information
Course title POWER ELECTRONICS FOR RENEWABLE ENERGY SOURCES
Field of study Electrical engineering, automatic control systems, industrial electronics, energy,
mechatronics
Teaching method lecture / project
Person responsible for
the course
Marcin Hołub
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 3
Type of course Obligatory Level of course bachelor
Semester winter or summer Language of instruction English
Hours per week 1Lecture / 2Project Hours per semester 15 Lecture
30 Project
Objectives of the
course
Student will be able to:
- recognize and distinguish basic types of renewable electrical energy sources.
- distinguish basic characteristics of different sources.
- distinguish basic types of photovoltaic modules and their main properties, will be
able to draw basic waveforms.
56
- distinguish basic types of solar converters.
- give basic properties and characteristics for main types of switched mode power
supplies.
- perform basic calculations for main circuit components and adjust component
type and kind.
- use CAD software for basic simulations and basic types of projects.
- perform basic project for a small scale power converter.
- analyze basic structures of power converters and draw main schematics for system
components.
Entry requirements/
prerequisites Electronics, basics of electrical engineering
Course contents
Power electronics for renewable energy sources: past and present of energy production and
consumption, perspectives, connections with other technical branches. Basic electrical and
eletromechanical properties of photovoltaic panels and modules. Fuel cells – construction,
properties, dynamic response. Wind energy – basics, Betz’s limit, basic constructions. Power
electronic converters for energy conversion. Switched mode power supplies, MPP tracking.
Single and three phase inverters. Converter groups for photovoltaic systems, wind energy
converters. Grid connection. Summary.
Assessment methods Written tests
Project work assessment
Learning outcomes
Ability to distinguish properties and characteristics of various renewable energy sources.
Ability to define proper power electronic converter chain. Ability to construct small – scale
converters for PV modules. Ability to construct simple simulation models. Ability to prepare,
set-up and conduct measurements and draw conclusions.
Required readings
1. K. Billings, T. Morey, Switching power supply design, ISBN 978-0-07-148272-1McGrawHill
2009
2. K. Billings, Switchmode power supply handbook, ISBN 0-07-006719-8McGrawHill 1999
3. M. H. Rashid, Power Electronics Handbook, Elsevier 2007, ISBN-13: 978-0-12-088479-7
Supplementary
readings
Additional information
Course title POWER SYSTEM ENGINEERING
Field of study Power Engineering
Teaching method
The lectures and laboratories are going in parallel. During lectures, the teacher, using classic
whiteboard and presentation, will teach about power electric system in Poland. During
laboratories students will have possibility to verify their knowledge about power electric
system and simulate its behavior using real models of network in laboratory.
Person responsible for
the course Dr inż. Michał Balcerak
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 3
Type of course Obligatory Level of course bachelor
57
Semester Winter or summer Language of instruction English
Hours per week 2 L / 2 Lab Hours per semester 30 L / 20 Lab
Objectives of the
course
Student has knowledge on power electric network – how it works, how to generate power
for electric consumer, what the properties of electric load are and witch of them are
important for the power system.
Entry requirements
/prerequisites
Student should know math (trigonometric and complex numbers) and basics of Electric
Engineering.
Course contents
Electric loads: power factor, current distortion factor,
Electric grid properties: impedance of electric grid, voltage drop, voltage losses and power
loses on the wires,
Correct methods of current, voltage and power measurement in three phase grid,
Generation and distribution of power
Assessment methods Laboratories measurement report assessment and final test on the end of the course
Lectures final written exam
Learning outcomes
Students will know:
- types of power plant, methods to produce energy in conventional and unconventional
power plant
- typical and distributed types of electric power grid
- method of reactive power compensation (Q), influence of Q to a loos of voltage and
power in power electric grid
- how to stabilize frequency and voltage in grid
- methods to decrease levels of higher harmonics of voltage and current in power electric
systems
- about power electronics devices in power electric grid: HVDC grids, PFC, distortion
reduction
Required readings
Supplementary
readings
1. D.P. Kothari, I.J. Nagrath, Power System Engineering, Tata McGraw-Hill Education, 2008
2. S. Sivabagaraju, S. Satyanarayana, Electric Power Transmission and Distribution, Pearson
Education 2009
3. D.F. Warne, Newnes Electrical Power Engineer's Handbook, 2005, ELSEVIER
4. Alexander S. Graffeo, The Electrical Engineer's Guide to passing the Power PE Exam,
2012
Additional information Maximum 12 persons in one laboratory group.
Course title POWER SYSTEM PROTECTION
Field of study Electrical engineering
Teaching method Lecture/laboratory
Person responsible for
the course Michał Zeńczak
E-mail address to the person
responsible for the course [email protected]
58
Course code
(if applicable) ECTS points 2
Type of course Obligatory/elective Level of course Bachelor
Semester Winter or summer Language of instruction English
Hours per week 1/1 Hours per semester 15/15
Objectives of the
course
Knowledge about principles of power system protection,
Skills of selection of protection for basic components of power system.
Entry requirements/
prerequisites Mathematics, physics, basis electrical engineering.
Course contents
Interferences in power system, overload protection, overcurrent protection, overvoltage
protection, undervoltage protection, differential protection, directional protection, distance
protection, protection of transformers, protection of lines, protection of busbars, protection
of generators, protection of electrical motors, investigation of overcurrent protection,
investigation of overvoltage protection, investigation of undervoltage protection,
investigation of distance protection, investigation if differential protection.
Assessment methods Continuous assessment in laboratory, final test on the end of lectures
Learning outcomes
Knowledge:
Student has knowledge for understanding principles of protection for basic components of
power system,
Skills:
Student is able to choice the protections for basic components of power system,
Required readings
Supplementary
readings
1. Grainger J.J., Stevenson W.D.: Power System Analysis, McGAW-HILL
2. INTERNATIONAL EDITIONS, 1994,
3. Grigsby L.L.: The Electric Power Engineering Handbook, CRC PRESS, 1998,
4. Grigsby L.L.: Electric Power Generation, Transmission, and Distribution, CRC PRESS,
2007,
5. Saccomanno F.: Electric Power Systems, Analysis and Control, John Wiley&Sons, 2003,
6. Weedy B.M., Cory B.J.: Electric Power Systems, John Wiley&Sons, 1998,
7. Northcote-Green J., Wilson R.: Control and Automation of Electrical Power Distribution
Systems, Taylor&Francis, 2007
Additional information
Course title PROBLEM-SOLVING WORKSHOP
Field of study
Teaching method
lab and project work, seminars
59
Person responsible for
the course Joanna Górecka
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 5
Type of course compulsory Level of course bachelor or master
Semester winter or summer Language of instruction English
Hours per week
4 (2Lab, 1P, 1S-average) Hours per semester 60 (30Lab, 15P, 15S)
Objectives of the
course
To provide knowledge on research and design methods and to develop various skills useful
in solving bioengineering problems.
Entry requirements/
prerequisites
Physics, Informatics, Signal processing, Image processing, Telecommunications, Computer
Systems, Biomedical Engineering, fundamentals of semiconductor electronics.
Course contents
Research work (individual or in 2-3 students teams) is run on topics corresponding to the
area of all courses. The topics are offered by the teachers and chosen by the students at the
beginning of the semester, after consultations; the topics may be also proposed by the
students. Projects are run using all facilities of the Department of Systems, Signals and
Electronics Engineering and co-operating Departments (including rooms, laboratory
equipment, computers & software, Internet access, library, copying facilities etc.).
Consultations with supervisors – the teachers involved in all projects - are performed
regularly during the semester, with presentation of the progress of research work in the mid
of the semester, in a form of a seminar open for all students and teachers (6h). Final
assessment of a particular project is made after evaluation of the written report by the
supervisor and reviewer, on the basis of oral presentation or a poster during the second,
final seminar (9h) .
Assessment methods Continuous assessment of lab and project work, evaluation of the written report and of
oral/poster presentation of the project results during the final seminar.
Learning outcomes
The student has knowledge on research and design methodology, and on performing
project work. He has practical skills useful in solving interdisciplinary problems in the field of
biomedical engineering.
Required readings Recommended materials for all courses of the SPE-1 program in BME.
Supplementary
readings Recommended materials for all courses of the SPE-1 program in BME .
Additional information -
Course title PROGRAMMABLE AUTOMATION SYSTEM BASED ON PLC AND HMI
Field of study
Automatic Control and Robotics, Electrical Engineering, Mechanical Engineering,
Management and Production Engineering , Information and Communications Technology,
Electronics and Telecommunications, Architecture and Urban Planning - Civil Engineering
60
Teaching method Lecture, project, laboratory
Person responsible for
the course Krzysztof Jaroszewski
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 3
Type of course Compulsory/optional Level of course bachelor
Semester Winter or summer Language of instruction English
Hours per week 1 (L) 1 (P) 1 (Lab) Hours per semester 1 (L) 1 (P) 1 (Lab)
Objectives of the
course
To form skills of programming automation system consists of: Programming Logical
Controllers (PLC’s) - in the control level and Human Machine Interfaces (HMI’s) – in maintain
level. Moreover, subject with diagnostic and fault tolerant control algorithms will be bring
closer. During practical parts of the course SIMATIC by SIEMENS devices will be used: PLC:
S7-1200, HMI: KTP600.
Entry requirements/
prerequisites Elementary knowledge in the subject of mathematical logic
Course contents
Automatic systems – basic knowledge. Programmable devices in automaton of industrial
processes: PLC, HMI, SCADA, DCS and their tasks. PLC’s programming languages and
cycled operating. Diagnostic of industrial processes methods.
Assessment methods Grade
Project work
Learning outcomes Ability to design automation system including elementary diagnostics and built project on
PLC and HMI.
Required readings
Curse materials
Manuals by SIEMENS
Automating with SIMATIC S7-1200: Configuring, Programming and Testing with STEP 7
Basic, Hans Berger, ISBN: 978-3-89578-901-4
Supplementary
readings
1. Programmable Logic Controllers: An Emphasis on Design and Application, Kelvin T.
Erickson, ISBN-13: 978-0976625926
Additional information Max 12 persons.
Course title PROGRAMMABLE LOGIC DEVICES
Field of study
Electronics and Telecommunications
Automatic Control and Robotics
Electrical Engineering
Teaching method lectures, laboratory, project
Person responsible for
the course Witold Mickiewicz
E-mail address to the person
responsible for the course [email protected]
61
Course code
(if applicable) ECTS points 4
Type of course compulsory Level of course Bachelor, master
Semester Winter or Summer Language of instruction English
Hours per week 1L/1Lab/1Project Hours per semester 15L/ 15Lab/ 15Project
Objectives of the
course
To provide knowledge on programmable logic devices and its use in modern digital system
design
Entry requirements/
prerequisites Basic knowledge on digital circuits and informatics
Course contents
Lectures: Categorization of programmable logic devices. Design systems for SPLD and
CPLD. Configuration memory. ABEL. Properties and configuration of logic blocks (LUT, FF)
and I/O in FPGA. Specialized blocks – RAM, multipliers. Distribution of clock signals (PLL,
DLL). Metastability. Abstraction levels in digital systems description. Elements of VHDL in
synthesis of digital systms. Designing paths. Design environments for FPGA design. JTAG.
Systems on Chip. Structured ASIC.
Labs: PLD synthesis using VHDL and laboratory boards.
Project: Design and testing of various digital systems designed using FPGA laboratory
boards.
Assessment methods Written exam, accomplishment of practical labs and projects
Learning outcomes
Student will be able to describe the building blocks in modern CPLD and FPGA integrated
circuits. Student will be able to design and test simple digital appliances using
programmable IC's and hardware description language.
Recommended
readings
1. Skahill K.: VHDL. Design of programmable logic devices. Prentice Hall 2001
2. Sunggu Lee, Design of computers and other complex digital devices, Prentice Hall 2000
3. Perry D. L.: VHDL. McGrawHill, 1997.
Supplementary
readings
1. Oldfield J. V., Dorf R. C.: FPGAs. Reconfigurable Logic for Rapid Prototyping and
Implementation of Digital Systems. John Wiley&Sons, Inc., N.Y., 1995.
2. Xilinx data sheets and programmer literature at www.xilinx.com.
Additional information
Course title RENEWABLE ENERGY SOURCES
Field of study Power Engineering, Renewable Energy Sources
Teaching method The teacher, using PowerPoint presentation, movies and classic whiteboard, will teach about
small and large renewable energy sources for power electric grid.
Person responsible for
the course Dr inż. Michał Balcerak
E-mail address to the person
responsible for the course [email protected]
62
Course code
(if applicable) ECTS points 2
Type of course Obligatory Level of course bachelor
Semester winter/summer Language of instruction English
Hours per week 2L Hours per semester 30 L
Objectives of the
course
Student has knowledge on method of power generation – how a power plants works and
what’s the methods of energy storage.
Entry requirements/
prerequisites
Student should know math (trigonometric and complex numbers) and basics of Electric
Engineering and Electric Motors.
Course contents
Description of followed power plants: conventional, photovoltaic, wind, water, solar, nuclear,
fusion, geothermic, biomass, etc.
Description of energy storage methods for domestic and large-scale grids.
Assessment methods Final test on the end of the course
Learning outcomes
Students will know:
- types of power plant, methods to produce energy in conventional and unconventional
power plant
- methods of storage the energy for small- and large-scale electric grid.
Required readings
Supplementary
readings
Additional information
Course title REQUIREMENTS MANAGEMENT IN RESEARCH PROJECTS ON COMPLEX
SYSTEMS
Field of study Control Engineering, ICT
Teaching method Lectures, simple examples; Lab – software tools learning with examples; Project – computer
modeling
Person responsible for
the course Krzysztof Pietrusewicz
E-mail address to the
person responsible for
the course
Course code
(if applicable) ECTS points 3
Type of course Obligatory Level of course Bachelor/Master
Semester Winter or summer Language of
instruction English
Hours per week 1 Lecture, 1 Lab, 1 Project Hours per semester 15 Lecture, 15 Lab, 15 Project
63
Objectives of the
course
This course is intended to present basics of requirements management, software tools and
methods for effective tracing and change management of initial requirements within
interdisciplinary research projects of complex systems.
Entry requirements/
prerequisites Mechatronics, Control theory, Computer science
Course contents
1. Definition of project requirements 2. gathering requirements from stakeholders within
interdisciplinary project (bridge between Universities and industries, understanding goals
issues) 3. Graphical modeling of project requirements 4. Requirements traceability and
change issues 5. Workflows models for interdisciplinary research teams, including
approaches for teams with different experience level
Assessment methods Lectures – project public presentation during seminar, Lab – validation on preparation level,
Project – continuous assessment
Learning outcomes
After this course student is able to:
1. identify and model requirements, including prioritization of requirements stated
2. understand influence of modeling requirements for team efficiency as compared with
classic realization of projects
3. understand the need of requirements traceability during development of control software
for complex mechatronic systems
Required readings
1. Holt J., Perry S.A., Brownsword M., Model-based requirements engineering, 2012, ISBN
978-1-84919-487-7
2. ISO/IEC/IEEE 29148:2011, Systems and software engineering - Life cycle processes -
Requirements engineering. 2011
Supplementary
readings
1. The Official OMG SysML website, http://www.omgsysml.org/
2. Papyrus UML for Eclipse website, https://eclipse.org/papyrus/
3. Visual Paradigm website, http://www.visual-paradigm.com/
4. Sparx Enterprise Architect website, http://www.sparxsystems.com.au/
Additional information
Course title ROBOT DYNAMICS AND CONTROL
Field of study Automatic control and robotics
Teaching method Lecture / laboratory
Person responsible for
the course Rafał Osypiuk
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 2
Type of course Optional Level of course Master
Semester Summer Language of instruction English
Hours per week 1 (L) 1 (Lab) Hours per semester 15 (L) 15 (Lab)
64
Objectives of the
course
The student will gain competences related to evaluation of complex process, including their
non-linearity or time-varying nature and methods of elimination thereof, both during the
robotic-arm design and during control system synthesis. Additionally, the student will gain
the ability to choose the appropriate control structure and to verify its property through
low-level use of the simulation environment.
Entry requirements/
prerequisites Mathematics, Mechanics, Introduction to robotics, Programming languages
Course contents
The course includes selected topics of dynamics modelling and position control methods
related to industrial robots. In particular, the course discusses mathematical description of a
robotic-arm in the presence of forces/torques and methods of its used in implementations
of advanced control systems. Functional blocks for the Matlab/Simulink environment are
prepared using C programming language, which help to analyse various control strategies,
from a single-loop PID structure to multi-loop solutions with many degrees of freedom.
Assessment methods Grade / project work
Learning outcomes
The ability to modelling of robot dynamics on the basis of mathematical analysis and
correct interpretation of physical phenomena occurring within a kinematic chain. Skills to
implement, simulate and analyse simple and complex control systems, in particular
structures based on forward or inverse plant model.
Required readings
1. Spong M. W., Hutchinson S., and Vidyasagar M., Robot Dynamics and Control,
Introduction to Robotics: Mechanics and Control, 2004, 2nd Edition
2. Craig J. J., Introduction to Robotics: Mechanics and Control , 2004, 3rd Edition
Supplementary
readings
1. Kozłowski K., Modelling and Identification in Robotics, 1998, 1st Edition
2. Siciliano B, Villani L, Robot Force Control, 1999, 1st Edition
3. Siciliano B., Khatib O., Springer Handbook of Robotics, 2008, 1st Edition
Additional information Max 6 persons.
Course title SELECTED TOPICS IN NONLINEAR PHOTONICS
Field of study
Electronics and Telecommunications,
Automatic Control and Robotics,
Electrical Engineering ,
Teleinformatics
Teaching method Lecture + laboratory
Person responsible for
the course Prof. Ewa Weinert-Raczka
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable)
ECTS points 2
Type of course facultative Level of course master
Semester summer Language of instruction English
Hours per week 1h-lecture, 1h-laboratories
Hours per semester
15h—lecture
15h-laboratories
65
Objectives of the
course
The first objective of this course is to give basic optics and photonics concepts related to
nonlinear optical phenomena
Entry requirements/
prerequisites Basics knowledge in mathematics and physics
Course contents
Nonlinear optical phenomena and their applications: basics of nonlinear photonics,
nonlinear materials, new frequencies generation, phase conjugating mirrors and wavefront
reconstruction, all-optical switching, nonlinear waveguides, temporal and spatial soliton
propagation, reconfigurable photonic circuits, supercontinuum generation.
Assessment methods Lecture, numerical simulations
Learning outcomes At successful completion of this course the students will be familiar with basics of nonlinear
optics and nonlinear photonics applications.
Required readings
1. B. E. A. Saleh, M. C. Teich, Fundamentals of Photonics, Wiley Series in Pure and Applied
Optics, 2007
2. Y. S. Kivschar, G. P. Agrawal, "Optical solitons - From Fibers to Photonic Crystals", Elsevier,
London 2003
Supplementary
readings
Additional information
Course title SIMULATION AND DESIGN OF POWER ELECTRONIC CONVERTERS
Field of study Electrical engineering, automatic control systems, industrial electronics, mechatronics,
robotics
Teaching method Project / classes
Person responsible for
the course Marcin Hołub
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 3
Type of course Obligatory Level of course master
Semester winter or summer Language of instruction English
Hours per week 1 Classes /2Proj Hours per semester 15 Classes /30 Proj.
Objectives of the
course
Student will recognize and distinguish basic switch mode power supply systems. Will learn
how to approach project tasks, deal with projects. Will learn how to simulate (in time
domain, thermal domain and frequency domain) power electronic converters in different
environments. Will learn how to calculate converter components, including magnetics. Will
obtain knowledge on CAD design of power electronic converters. Will get experience in
constructing prototypes, measurement techniques, error elimination methods.
66
Entry requirements/
prerequisites Basics of electrical engineering, basics of power electronics, basics of automatic control
Course contents
1. Project approach and solution theory
2. SMPS converters – non-isolated
3. SMPS converters – isolated topologies
4. Basics of magnetics – inductor
5. Exemplary project calculations
6. Basics of magnetics – HF transformers
7. CAD design rules
8. Prototype construction methods
Assessment methods Project assessment and presentation
Learning outcomes
Ability to calculate and analyze basic SMPS, ability to calculated component values for
different converter topologies. Ability to design and construct simple, power electronic
solutions. Knowledge on prototype testing methods and practical measurements. Ability to
present own work and use technical language.
Required readings
1. M. H. Rashid, Power Electronics Handbook, Elsevier 2007, ISBN-13: 978-0-12-088479-
7
2. Bimal Bose, Power electronics and motor drives, Elsevier 2006, ISBN-13 978-0-12-
088405-6
3. K. Billings, T. Morey, Switching power supply design, ISBN 978-0-07-148272-
1McGrawHill 2009
4. K. Billings, Switchmode power supply handbook, ISBN 0-07-006719-8McGrawHill
1999
Supplementary
readings
Additional information
Course title SOUND SYSTEM DESIGN
Field of study
Electronics and Telecommunications
Automatic Control and Robotics
Electrical Engineering
Teaching method lectures, seminar, laboratory
Person responsible for
the course Witold Mickiewicz
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 4
Type of course optional Level of course bachelor, master
Semester winter or summer Language of instruction English
67
Hours per week 1L/1S/2Lab Hours per semester 15L/15S/30Lab
Objectives of the
course To provide knowledge and design skills in various sound systems engineering.
Entry requirements/
prerequisites Basic knowledge in Physics and Electronic circuits
Course contents
Lectures: Acoustic wave propagation. The decibel scale. Loudspeakesr and enclosures.
Directivity and angular coverage of loudspeakers. Microphones. Outdoor sound
reinforcement systems. Fundamentals of room acoustics. Behavior of sound systems
indoors. Sound system architectures and its elements. Multichannel hi-fi and cinema sound
systems. Public address and conference systems. Car audio.
Seminar: complementary calculation exercises
Labs: Loudspeaker measurements and design. Room acoustics measurements and
acoustical adaptation design. Microphones measurements and setup. Various sound system
design. Using microphones, loudspeakers, amplifiers, mixing console and sound effects in
sound reinforcement system design. Case studies.
Assessment methods Written exam, accomplishment of practical labs
Learning outcomes Knowledge and skills in designing and maintenance of sound systems of various scale and
features.
Required readings
1. Davis D. and C.: Sound System Engineering. Second edition, Howard F. Sams,
Indianapolis, 1987.
2. JBL Professional, Sound System Design Reference Manual,
pdf document available at www.jblpro.com.
Supplementary
readings 1. Eargle J.: Electroacoustical Reference Data. Van Nostrand Reinhold, New York, 1994.
Additional information
Course title STATISTICAL METHODS IN ICT
Field of study ICT
Teaching method Lecture + project
Person responsible for
the course Przemyslaw Włodarski
E-mail address to the
person responsible for
the course
Course code
(if applicable) ECTS points 5
Type of course Optional Level of course Bachelor
Semester Winter or summer Language of instruction English
68
Hours per week 2 lect. / 2 proj. Hours per semester 30 lect. / 30 proj.
Objectives of the course This course is intended to present statistical methods in ICT for analysis and modeling
purposes.
Entry requirements/
prerequisites Mathematics, basics of computer networks.
Course contents
Statistical data analysis, random variables, distributions, stochastic processes. Traditional
models in Telecommunication Networks: Poisson, Markov Modulated Poisson Process
(MMPP). Estimation of self-similarity in computer networks: R/S analysis, variance-time plot,
Index of Dispertion for Counts (IDC), peridogram and wavelet analysis, Whittle and local
estimators. Self-similar models of network traffic: superposition of heavy-tailed on/off
sources, FARIMA processes, Pareto Modulated Poisson Process (PMPP), Markov Modulated
Bernouli Process (MMBP), circulant embedded matrix method, Spatial Renewal Processes
(SRP), methods based on power spectrum of fractional Gaussian noise. Queueing models in
telecommunication networks: M/M/1/(K), M/D/1/(K), M/G/1/(K), G/M/1/(K), G/G/1/(K).
Generation of self-similar traffic using traditional and self-similar models.
Assessment methods Written exam (test), project work
Learning outcomes Knowledge of web development basics, including front-end as well as back-end side. Ability
to create web pages from scratch.
Required readings
1. Medhi J., Stochastic models in queueing theory. Academic Press, 2nd edition, 2002.
2. Gross D., Harris C.M., Fundamentals of queueing theory. Wiley-Interscience, 3rd edition,
1998.
3. Park, K., Willinger, W., Self-similar network traffic and performance evaluation. John Wiley
& Sons, 2000.
Supplementary
readings
1. Krishna M., Gadre V., Desai U.: Multifractal Based Network Traffic Modeling, Springer
Science & Business Media, 2003.
Additional information
Course title TELEMEDICINE
Teaching method lectures, lab training, computer simulations
Person responsible for
the course Sławomir Kocoń
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 3
Type of course compulsory Level of course master
Semester winter or summer Language of instruction English
Hours per week 4 (2L, 2Lab) Hours per semester 45 (30L, 30Lab)
69
Objectives of the
course
To provide actual knowledge on information technologies in biomedical applications and to
develop design skills in this field
Entry requirements Informatics, Computer systems, Telecommunications, Networking, Fundamentals of
Biomedical Engineering
Course contents
Lectures: Hospital and hospital information system (HIS), basic concepts of HIS on different
levels of hospital. Communication systems in healthcare. Clinical communication in
telemedicine. Electronic medical. Transfer of biomedical signals in telemedicine and its use
for stimulation devices. Internet applications in telemedicine. Reliability of health
information systems, electrical safety of medical devices and equipment. Human and
sociotechnical factors. Ethical and legal challenges. Evaluation of telemedicine systems.
Future trends in telemedicine.
Labs: Medical databases. HL7 systems. DICOM and PACS. WWW and video-conference
applications for telemedicine. Wireless transmission of biomedical signals. Biosensors
integration with Bluetooth and other modules. Wireless networks in hospitals, in
telemonitoring and teleassistance at home. Tele-service of medical equipment in hospitals
Assessment methods Written exam, accomplishment of practical labs
Learning outcomes
The student has increased knowledge on advanced information and communications
technologies in biomedical applications (equipment, software, specialized systems and
standards used in this field). He has practical skills useful in the area of IT&T technologies
used in e-Health regarding their development, implementation, exploitation and
assessment
Recommended
readings
1. Gordon C., Christensen J. P. (ed.): Health Telematics for Clinical Guidelines and Protocols.
IOS Press, Ohmsha, 1995
2. Mantas J. (ed.): Health Telematics Education. IOS Press, Ohmsha, 1997
3. Coiera E.: Guide to Medical Informatics. The Internet and Telemedicine. Arnold, London,
1997
4. Field M. J. (ed.): Telemedicine. A Guide to Assessing Telecommunications in Health Care.
National Academy Press, Wash. D.C., 1996
5. IT-EDUCTRA. FUNDESCO, Commission of the EC, 1998
6. Chronaki, C. E. (2004). Open ECG: Goals and achievements. Proceedings of the 2nd Open
ECG Workshop (pp. 3-4), Berlin.
7. Dolin, R. H., Alschuler, L., Boyer, S., & Beebe, C. (2004). HL7 clinical document
architecture. Release 2.0. HL7 Health Level Seven, Inc., Ann Arbor, MI. Available online
at: www.hl7.org
Additional information
Course title TERAHERTZ TECHNIQUE
Field of study Electrotechnics, electronics
Teaching method Lectures in form of multimedia presentation;
project – designing, measurements and computer simulations of terahertz devices/systems
Person responsible for
the course Przemyslaw Lopato
E-mail address to the person
responsible for the course [email protected]
70
Course code
(if applicable) - ECTS points 2
Type of course Obligatory Level of course bachelor/master
Semester Winter or summer Language of instruction English
Hours per week
2 hours
(lectures – 1, project – 1, other
organization is possible)
Hours per semester
30 hours
(lectures – 15,
project – 15)
Objectives of the
course
This course is intended to present a basic knowledge of terahertz technique and its
application in modern industry
Entry requirements/
prerequisites Basic course of mathematics and physics (electromagnetics)
Course contents
Generation and detection of EM waves in the THz frequency range. Passive devices in
terahertz technology. Materials properties and metamaterials in THz frequency range.
Application of terahertz technique in spectroscopy, imaging, biomedical engineering, public
safety and short-range wireless transmissions. Numerical modeling of terahertz systems.
Overview of available terahertz systems.
Assessment methods Lectures – oral exam; project – report assessment
Learning outcomes During the course, students will gain a basic knowledge of the operation, design and
modeling of measurement systems that use electromagnetic waves in the terahertz range.
Required readings 1. Yun-Shik Lee: Principles of Terahertz Science and Technology, Springer, New York 2009
2. Sakai K.: Terahertz optoelectronics, Springer, Berlin 2005
Supplementary
readings
1. Miles R. E., Harrison P., Lippens D.: Terahertz sources and systems, Kluwer, Dordrecht
2001
Additional information -
Course title ULTRASONIC AND RADIOGRAPHIC NONDESTRUCTIVE TESTING
Field of study Electrical Engineering, Computer Engineering, Electronic Engineering, Information
Technology Engineering, Automation and Robotics Engineering
Teaching method Lectures
Person responsible for
the course Marcin Ziółkowski
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 2
Type of course Obligatory Level of course Bachelor, Master
Semester Winter or summer Language of instruction English
71
Hours per week Lectures - 2 Hours per semester Lectures - 30
Objectives of the
course
This course is intended to present a unified approach to ultrasonic and radiographic
nondestructive testing.
Entry requirements/
prerequisites Mathematics, Physics
Course contents
1. Ultrasonic Principles.
2. Equipment Controls.
3. Wave Propagation.
4. Couplants, Material Characteristics, Beam Spread.
5. Attenuation, Impedance and Resonance.
6. Screen Presentations, Angle Beam Inspection with UT Calculator.
7. Transducers, Standard Reference Blocks.
8. Immersion Inspection.
9. Contact Testing, Longitudinal & Shear Waves, Snell’s Law.
10. Applications of Radiography.
11. Penetration and Absorption.
12. Radiographic Sensitivity.
13. Structure of the Atom.
14. X and Gamma Rays.
15. X-Ray Equipment.
16. Subject and Film Contrast.
17. Radiographic Film & Processing Techniques.
18. Radiation Hazard.
19. Permissible Radiation Dose.
20. Radiation Effects.
21. Protection Against Radiation.
22. Specialized Radiographic Equipment.
23. X-Ray Exposure Charts.
24. Specialized Techniques.
25. Discontinuities.
26. Practical Problem Solving.
Assessment methods Lectures – written exam; Laboratory – continuous assessment
Learning outcomes
Students will get the knowledge about Ultrasonic and Radiographic Nondestructive Testing
theory and practice. They will also know what kind of objects can be inspected with such
techniques.
Required readings
1. D. Van Hemelrijck, A. Anastassopoulos: Non Destructive Tersting, A.A. Balkema, 1996
2. http://www.ndt.org/
3. http://www.ndt-ed.org/EducationResources/CommunityCollege/communitycollege.htm
4. http://www.ndt.net/
Supplementary
readings
Additional information
72
Course title VISUAL PROGRAMMING IN LABVIEW
Field of Study
Automatic control and robotics; Electronics and telecommunication;
Information and communications technology;
Electrical engineering.
Teaching method Lectures, demonstrations, laboratory exercises
Person responsible for
the course dr inż. Paweł Dworak
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 3
Type of course optional Level of course bachelor
Semester Winter or summer Language of instruction English
Hours per week 1L, 2Lab Hours per semester 15L, 30Lab
Objectives of the
course
Teach students a graphical way of programming in LabVIEW. Preparation of students to the
CLAD certificate.
Entry requirements
/prerequisites Basics of programming.
Course contents
Introduction to LabVIEW environment. Navigating LabVIEW, Troubleshooting and
Debugging Vis, Implementing a VI, Developing Modular Applications, Creating and
Leveraging Data Structures, Managing File and Hardware Resources, Using Sequential and
State Machine Algorithms, Solving Dataflow Challenges with Variables, Moving Beyond
Dataflow, Implementing Design Patterns, Controlling the User Interface, File I/O Techniques,
Improving an Existing VI, Deploying an Application.
Assessment methods Continuous assessment.
Learning outcomes Students will be able to write programs in a graphical LabVIEW environment. Should be
able to pass the CLAD certification exam.
Required readings National Instruments documentation, NI forum
Supplementary
readings
Additional information
73
Course title WALKING ROBOTS
Field of study Automatic Control and Robotics
Teaching method
Lectures covering basic modelling of walking robots, analysis of walking patterns and
control methods. Laboratory course covering modelling and control of a walking robot,
using simulations and miniature two-legged and multi-legged robots.
Person responsible for
the course Adam Łukomski
E-mail address to the person
responsible for the course [email protected]
Course code
(if applicable) ECTS points 3
Type of course optional Level of course master
Semester Winter or summer Language of instruction english
Hours per week 1h lecture, 2h laboratory Hours per semester 15h lecture,
30h laboratory
Objectives of the
course The Student will learn to model and control a walking robot.
Entry requirements/
prerequisites Linear Control, Nonlinear Control, Basic Robotics
Course contents
Lectures cover the modelling (kinematics and dynamics) of multi-legged walking robots,
analysis of support phases, ground impacts, basic trajectory and path planning, and
nonlinear control design. Laboratory course covers simulation of walking robots and
implementation of control methods on miniature humanoid robot and multi-legged
walking robots.
Assessment methods Written exam (on last lecture), Continuous assessment during laboratory course
Learning outcomes Ability to model and control a walking robot.
Required readings 1. Chevallereau, Christine, et al., eds. Bipedal Robots: Modeling, Design and Walking
Synthesis. John Wiley & Sons, 2013.
Supplementary
readings
1. Westervelt, Eric R., et al. Feedback control of dynamic bipedal robot locomotion. Vol. 28.
CRC press, 2007.
2. Selig, Jon M. Geometric fundamentals of robotics. Springer, 2005.
Additional information