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Digital Signal Processing & Digital Signal Processing & Digital FiltersDigital Filters

An Introductory CourseBy

Professor A G ConstantinidesMSc, EE4, ISE4, PhD

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Contents

1-Introduction1) Introduction to Digital Signal Processing Review of background DSP Review of mathematical methods Review of discrete-time random

processes and linear systems

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2) Multirate techniques and wavelets Introduction to short-time Fourier analysis Filter-banks and overlap-add methods of analysis

and synthesis Introduction to generalised time-frequency

representation Wavelet analysis Multirate signal processing Interpolation and decimation Efficient filter structures for interpolation and

decimation

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3) Classical spectrum estimation methods Power spectrum, power spectral density functions,

random processes and linear systems Introduction to statistical estimation and estimators Biased and unbiased estimators Einstein/Wiener Khintchine Theorem Estimation of autocorrelations Means and variances of periodograms Smoothed spectral estimates, leakage

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4) Modern spectrum estimation methods Introduction to modern spectral estimation:

Principles and approaches Cramer-Rao Lower Bound (CRLB) and Efficient

estimators The Maximum Entropy Method (MEM) or

Autoregressive Power Spectrum Estimation: Principles.

The MEM equations and Levinson/Durbin algorithm

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4) Modern spectrum estimation methods (continued)

Introduction to Linear Prediction Linear Predictive Coding using covariances

and correlations Cholesky decomposition Lattice Filters Linear Prediction of Speech Signals

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5) Adaptive signal processing Introduction to adaptive signal processing Objective measures of goodness Least squares and consequences Steepest descent The LMS and RLS algorithms Kalman Filters

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6) Applications Communications Biomedical Seismic Audio/Music

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DIGITAL FILTERSDIGITAL FILTERSDigital Filters In this course you will learn: How to choose an appropriate filter

response. Why Butterworth responses are

maximally flat. Why Chebyshev and Elliptic responses

are equiripple. When to choose an IIR and when an FIR

filter

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DIGITAL FILTERSDIGITAL FILTERS How do you design FIR and IIR filters from

specifications on amplitude performance? What are multirate systems and their

properties? What is interpolation / Upsampling and Decimation / Downsampling?

How do you design efficient Decimation and Interpolation systems?

What are frequency transformations and how do you design these?

How accurate is the DFT as a spectrum estimator?

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DIGITAL FILTERSDIGITAL FILTERS What are short FFT algorithms? How do you choose the required

wordlength? What are Fast Convolutions and

how are they realised? How do you deal with a DSP

problem in practice?

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Course contentCourse contentAssumed DSP background

DSP Background folder 1-Introduction 2-z transform 3-transfer functions 4-Signal Flow Graphs 5-digital filters intro

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Course contentCourse content

2-Digital Filter Design 1-Digital Filters (FIR) 2-Digital Filters (IIR)

3-Multirate1-Interpolation_Decimation

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4-Tranforms 1-DFT 2-DFT_one2two 3-general transforms 4-Wavelets

5-Finite Wordlength 1-Finite Wordlength

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Course contentCourse content6-Spectrum Estimation (Assumed

background in Mathematical Background folder)

1-Fourier transform & DFT 2-FFT-based Power Spectrum Estimation 3-Modern Spectrum Estimation 4-Intro-Estimation 5-Eigen-based methods 6-A Prediction Problem

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7-Adaptive Signal Processing 1-Adaptive Signal Processing

8-Applications 1-Applications 2-Applications

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BOOKS Main Course text books: Digital

Signal Processing: A computer Based Approach, S K Mitra, McGraw Hill

Mathematical Methods and Algorithms for Signal Processing, Todd Moon, Addison Wesley

Other books: Digital Signal Processing, Roberts &

Mullis, Addison Wesley Digital Filters, Antoniou, McGraw Hill

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DIGITAL FILTERSDIGITAL FILTERSAnalogue Vs Digital Signal Processing Reliability:Analogue system performance degrades

due to: Long term drift (ageing) Short term drift (temperature?) Sensitivity to voltage instability. Batch-to-Batch component variation. High discrete component count

Interconnection failures

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DIGITAL FILTERSDIGITAL FILTERSDigital Systems: No short or long term drifts. Relative immunity to minor power

supply variations. Virtually identical components. IC’s have > 15 year lifetime Development costs System changes at

design/development stage only software changes.

Digital system simulation is realistic.

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DIGITAL FILTERSDIGITAL FILTERS

Power aspects Size Dissipation

DSP chips available as well as ASIC/FPGA realisations

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ApplicationsApplications

Radar systems & Sonar systems Doppler filters. Clutter Suppression. Matched filters. Target tracking. Identification

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Image Processing Image data compression. Image filtering. Image enhancement. Spectral Analysis. Scene Analysis / Pattern

recognition.

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Biomedical Signal Analysis Spatial image enhancement. (X-

rays) Spectral Analysis. 3-D reconstruction from projections. Digital filtering and Data

compression.

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Music Music recording. Multi-track “mixing”. CD and DAT. Filtering / Synthesis / Special

effects.

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Seismic Signal Analysis

Bandpass Filtering for S/N improvement.

Predictive deconvolution to extract reverberation characteristics.

Optimal filtering. (Wiener and Kalman.)

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DIGITAL FILTERSDIGITAL FILTERSTelecommunications and Consumer

ProductsThese are the largest and most

pervasive applications of DSP and Digital Filtering

Mobile Communications Digital Recording Digital Cameras Blue Tooth or similar

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