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

2. Digital Signal Processing & Digital Filters
Contents
1-Introduction
1) Introduction to Digital Signal Processing
Review of background DSP
Review of mathematical methods
Review of discrete-time random processes and linear systems
Professor A G Constantinides©

3. Digital Signal Processing & Digital Filters
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
Professor A G Constantinides©

4. Digital Signal Processing & Digital Filters
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
Professor A G Constantinides©

5. Digital Signal Processing & Digital Filters
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
Professor A G Constantinides©

6. Digital Signal Processing & Digital Filters
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
Professor A G Constantinides©

7. Digital Signal Processing & Digital Filters
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
Professor A G Constantinides©

8. Digital Signal Processing & Digital Filters
6)  Applications
Communications
Biomedical
Seismic
Audio/Music
Professor A G Constantinides©

9. Professor A G Constantinides©
DIGITAL FILTERS
Digital 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
Professor A G Constantinides©

10. Professor A G Constantinides©
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?
How accurate is the DFT as a spectrum estimator?
Professor A G Constantinides©

11. Professor A G Constantinides©
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?
Professor A G Constantinides©

12. Professor A G Constantinides©
Course content
Assumed DSP background
DSP Background folder
1-Introduction
2-z transform
3-transfer functions
4-Signal Flow Graphs
5-digital filters intro
Professor A G Constantinides©

13. Professor A G Constantinides©
Course content
2-Digital Filter Design
1-Digital Filters (FIR)
2-Digital Filters (IIR)
3-Multirate
1-Interpolation_Decimation
Professor A G Constantinides©

14. Professor A G Constantinides©
Course content
4-Tranforms
1-DFT
2-DFT_one2two
3-general transforms
4-Wavelets
5-Finite Wordlength
1-Finite Wordlength
Professor A G Constantinides©

15. Professor A G Constantinides©
Course content
6-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
Professor A G Constantinides©

16. Professor A G Constantinides©
Course content
 7-Adaptive Signal Processing
1-Adaptive Signal Processing
8-Applications
1-Applications
2-Applications
Professor A G Constantinides©

17. Digital Signal Processing & Digital Filters
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
Professor A G Constantinides©

18. Professor A G Constantinides©
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
Professor A G Constantinides©

19. Professor A G Constantinides©
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.
Professor A G Constantinides©

20. Professor A G Constantinides©
DIGITAL FILTERS
Power aspects
Size
Dissipation
DSP chips available as well as ASIC/FPGA realisations
Professor A G Constantinides©

21. Professor A G Constantinides©
Applications
Radar systems & Sonar systems
·        Doppler filters.
·        Clutter Suppression.
·        Matched filters.
·        Target tracking.
Identification
Professor A G Constantinides©

22. Professor A G Constantinides©
DIGITAL FILTERS
Image Processing
 Image data compression.
Image filtering.
Image enhancement.
Spectral Analysis.
Scene Analysis / Pattern recognition.
Professor A G Constantinides©

23. Professor A G Constantinides©
DIGITAL FILTERS
Biomedical Signal Analysis
Spatial image enhancement. (X-rays)
Spectral Analysis.
3-D reconstruction from projections.
Digital filtering and Data compression.
Professor A G Constantinides©

24. Professor A G Constantinides©
DIGITAL FILTERS
Music
 Music recording.
Multi-track “mixing”.
CD and DAT.
Filtering / Synthesis / Special effects.
Professor A G Constantinides©

25. Professor A G Constantinides©
DIGITAL FILTERS
Seismic Signal Analysis
 Bandpass Filtering for S/N improvement.
Predictive deconvolution to extract reverberation characteristics.
Optimal filtering. (Wiener and Kalman.)
Professor A G Constantinides©

26. Professor A G Constantinides©
DIGITAL FILTERS
Telecommunications and Consumer Products
These are the largest and most pervasive applications of DSP and Digital Filtering
Mobile Communications
Digital Recording
Digital Cameras
Blue Tooth or similar
Professor A G Constantinides©