1. Digital Signal Processing & Digital Filters
An Introductory Course By
Professor A G Constantinides
MSc, EE4, ISE4, PhD 1

2. DIGITAL FILTERS In this course you will learn:
What are the general properties of a digital filter transfer function and amplitude response?
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 2

3. DIGITAL 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 from performance specifications?
How accurate is the DFT as a spectrum estimator? 3

4. DIGITAL 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? 4

5. Course content 1-Introduction 19 2-z transform 17
3-transfer functions 36
4-Signal Flow Graphs 25
5-digital filters intro 18
6-Digital Filters (FIR) 40
7-Digital Filters (IIR) 28
8-DFT 5

6. Course content 9-DFT_one2two 29 10-Fourier transform & DFT 14
11-general transforms 10
12-running DFT 05
13-convolutions & transforms 07
14-interpolation_decimation 32
15-Finite Wordlength 27
16-applications 27 6

7. Course content Filter Characteristics (Introductory)
·        General Amplitude responses.
·        Filter Characteristics
Butterworth
Chebyshev
Elliptic
·        Interpreting Filter Specifications.
·        The Bilinear z-Transform.
·        Frequency Transformations.
Design Demonstrations. 7

8. DIGITAL FILTERS FIR Filters, Structures and Design
·        Lowpass Prototypes.
·        Symmetry Conditions.
·        Review of Windows.
·        Optimisation Techniques for FIR filter Design.
·        Realisation models.
·        Differentiator and Hilbert Transform.
·        Design Examples
Design Demonstrations 8

9. DIGITAL FILTERS Multi-rate FIR and IIR Filters
·        What is multirate filtering and why the need?
·        Downsampling / Upsampling.
·        Polyphase filtering techniques.
·        Interpolation / Decimation.
·        General Sample Rate Change.
·        Design Examples.
Applications 9

10. DIGITAL FILTERS The Discrete Fourier Transform and the FFT
· Review and Definitions.
· Zero packing; zero extending.
· Radix 2/4/8 & Arbitrary Radix Transforms.
· Cook-Toom Algorithm.
· Thomas-Good Algorithm; The Chinese Remainder Theorem.
· Winograd Fourier Transforms.
· Prime Radix Transforms and Consequences.
· Wordlength; Scaling.
· Design Procedures in practice. 10

11. DIGITAL FILTERS InThe DFT as a Filtering Operator
·        Review of Fast Convolutions.
·        Cyclic and Acyclic Convolutions.
·        Overlap Add; Overlap Save.
·        Narrow Band Filter Banks.
·        Autocorrelation, Crosscorrelation.
·        Performance measures. 11

12. DIGITAL FILTERS
BOOKS
Course text book: Digital Signal Processing: A computer Based Approach, S K Mitra, McGraw Hill
Other books:
Introduction to Digital Signal Processing, Kuc, McGraw Hill
Digital Signal Processing, Roberts & Mullis, Addison Wesley
Digital Filters, Antoniou, McGraw Hill 12

13. DIGITAL FILTERS Analogue 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 13

14. DIGITAL FILTERS Digital 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.
DSP chips available as well as ASIC realisations 14

15. DIGITAL FILTERS
Power aspects
Size
Dissipation 15

16. Applications Radarsys / Sonarsys · Doppler filters.
·        Doppler filters.
·        Clutter Suppression.
·        Matched filters.
·        Target tracking.
Identification 16

17. DIGITAL FILTERS Image Processing Image data compression.
Image filtering.
Image enhancement.
Spectral Analysis.
Scene Analysis / Pattern recognition. 17

18. DIGITAL FILTERS Biomedical Signal Analysis
Spatial image enhancement. (X-rays)
Spectral Analysis.
3-D reconstruction from projections.
Digital filtering and Data compression. 18

19. DIGITAL FILTERS Music Music recording. Multi-track “mixing”.
CD and DAT.
Filtering / Synthesis / Special effects. 19

20. DIGITAL FILTERS Seismic Signal Analysis
 Bandpass Filtering for S/N improvement.
Predictive deconvolution to extract reverberation characteristics.
Optimal filtering. (Wiener and Kalman.) 20

21. DIGITAL FILTERS In 21

22. DIGITAL FILTERS Telecommunications and Consumer Products
These are the largest and most pervasive applications of DSP and Digital Filtering
Mobile
Digital Recording
Digital Cameras
Blue Tooth or similar 22