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1 © 2014 The MathWorks, Inc.
Data Analysis with MATLAB
Dr. Frank Graeber
MathWorks Germany
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Technical Computing Workflow
Equations
Data Surface fitting
Share Access Explore & Create
Derivation & solving
Optimization
Report
Application
Report
Application
Share Access Reports and
Documentation
Outputs for Design
Applications
Explore & Create
Data Analysis Files
Hardware
Software Mathematical Modeling
Algorithm Development
Application Development
x y E = V
R
Equations
F = ma
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Application Areas
Computational Finance
Test and Measurement
Signal Processing and Communications
Control System Design and Analysis
Image Processing
Computational Biology
Technical Computing
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Key Industries
Aerospace and defense
Automotive
Biotech and pharmaceutical
Communications
Education
Electronics and semiconductors
Energy production
Financial services
Industrial automation
and machinery
Medical devices
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The Voices of MATLAB Users
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Challenge Locate buried unexploded ordnance while minimizing the
cost and time expended on unnecessary digging
Solution Use MATLAB to develop and refine algorithms for
detecting and classifying UXO from data acquired by
electromagnetic induction sensors
Results Up to 50% cost savings with 86% reduction in digs
Complex data analyzed and understood
Calculation time cut by almost 75%
Black Tusk Geophysics Detects and
Classifies Unexploded Ordnance
Data collection with an advanced metal detector.
Link to user story
“With MATLAB we have the
ability to optimize algorithms
for nonlinear data fitting and
the flexibility to create user
interfaces that display
complex information in a clear
way. This combination is a
real strength of our solution.”
Laurens Beran
Black Tusk Geophysics
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Challenge Accelerate the analysis of sound recordings from wind
tunnel tests of aircraft components
Solution Use MATLAB and Parallel Computing Toolbox to
re-implement a legacy program for processing acoustic
data, and cut processing time by running
computationally intensive operations on a GPU
Results Computations completed 40 times faster
Algorithm GPU-enabled in 30 minutes
Processing of test data accelerated
NASA Langley Research Center Accelerates
Acoustic Data Analysis with GPU Computing
Wind tunnel test setup featuring the Hybrid Wing
Body model (inverted), with 97-microphone phased
array (top) and microphone tower (left).
Link to user story
“Our legacy code took up to 40
minutes to analyze a single wind
tunnel test; by using MATLAB
and a GPU, computation time is
now under a minute. It took 30
minutes to get our MATLAB
algorithm working on the GPU—
no low-level CUDA programming
was needed.”
Christopher Bahr
NASA
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HKM Optimizes Just-in-Time
Steel Manufacturing Schedule
Challenge Optimize a steel production process to enable
consistent, just-in-time delivery
Solution Use MATLAB and Global Optimization Toolbox to
maximize throughput of more than 5 million tonnes of
steel annually
Results Algorithm development accelerated by a factor of 10
Optimization time cut from 1 hour to 5 minutes
Customer satisfaction increased
“C++, Java, or third-party optimization
solutions would have required us to
spend significantly more time in
development or to simplify our
constraints. Only MATLAB provided
the flexibility, scalability, development
speed, and level of optimization that we
required.”
Alexey Nagaytsev
Hüttenwerke Krupp Mannesmann
Link to user story
Manually reviewed plant schedule (left) and plant schedule
automatically optimized with MATLAB genetic algorithms (right). The
optimized schedule minimizes schedule conflicts (in red), meets
delivery dates, and achieves the target utilization rate.
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Commerzbank Develops Production Software
System for Calculating Derived Market Data
Challenge Compute a variety of derived market data from raw
market data
Solution Use MATLAB to read data from a data management
system in a Windows and Linux architecture, perform
analyses and optimizations, visualize results, and deploy
mission-critical calculations
Results Integration with existing system simplified
Implementation time reduced by months
Updates made in days, not weeks
Link to user story
Commerzbank headquarters in Frankfurt.
“Our solution required a Windows
client and Linux server software. We
used MATLAB to rapidly develop
both by taking advantage of
distributed computing, a MEX-file
interface to access our financial
data, and fast, built-in functions for
optimization, regression, and more.”
Julian Zenglein
Commerzbank
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Challenge Develop and implement an acoustic respiratory
monitoring system for wheeze detection and asthma
management
Solution Develop algorithms for detecting wheeze and ambient
noise in MATLAB, and use MATLAB Coder to generate
code from the algorithms for mobile devices and a web
server
Results Manual coding effort reduced
Algorithm development iterations accelerated
Code maintenance overhead reduced
iSonea Develops Mobile App and Server
Software for Wheeze Detection and
Asthma Management
“MATLAB enables us to rapidly
develop, debug, and test sound-
processing algorithms, and
MATLAB Coder simplifies the
process of implementing those
algorithms in C. There’s no other
environment or programming
language that we could use to
produce similar results in the same
amount of time.”
Mark Mulvey
iSonea
The AirSonea device, which connects to an asthma
patient’s smartphone and communicates with
wheeze analysis algorithms on iSonea’s server.
Link to user story
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Challenge Design and implement an embedded system for extracting
accurate information from noisy electrocardiogram signals
Solution Use MATLAB to develop an algorithm for removing
in-band noise, and use Fixed-Point Designer and
MATLAB Coder to implement it on an ARM Cortex-M
series processor
Results Development accelerated by 300%
Power and memory consumption minimized
Rigorous testing enabled
VivaQuant Accelerates Development and
Validation of Embedded Device for
Ambulatory ECG Sensing
“MATLAB, MATLAB Coder, and
Fixed-Point Designer enabled our
small team to develop a complex
real-time signal processing
algorithm, optimize it to reduce
power and memory requirements,
accelerate embedded code
implementation, and perform the
rigorous testing required for medical
device validation.”
Marina Brockway
VivaQuant
ECG snippet before and after processing with
VivaQuant’s embedded in-band noise removal algorithm.
Link to user story
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Challenge Teach mathematics and mathematical modeling to
students across multiple disciplines and two universities,
and prepare them to meet the needs of industry
Solution Integrate MATLAB throughout the core mathematics
curriculum and provide interdisciplinary exercises in
practical problem-solving
Results Interdepartmental collaboration improved
Students taught skills required by industry
Students self-identified as expert users
Chalmers University of Technology
Integrates MATLAB Throughout Core
Mathematics Curriculum
Chalmers University in Gothenburg, Sweden.
Link to user story
“We train our students to use
MATLAB as an interactive tool not
only for completing the assigned
exercises but also for investigating
mathematical problems and having
fun. We are increasing our focus
on interdisciplinary programs, and
MATLAB is perfect for integrating
mathematics with other subjects.”
Dr. Tommy Gustafsson
Chalmers University of Technology
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Data Analysis with MATLAB Key Takeaways
Accelerate algorithm and application development plus maintenance
Accelerate data processing with parallel or GPU computing
Improve results and your customers’ satisfaction
Accelerate algorithm and application development plus maintenance
Accelerate data processing with parallel or GPU computing
Improve results and your customers’ satisfaction
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15 © 2014 The MathWorks, Inc.