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AGC
DSP
Professor A G Constantinides© 1
Digital Signal Processing &
Digital Filters
An Introductory Course
By
Professor A G Constantinides
MSc, EE4, ISE4, PhD
AGC
DSP
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
AGC
DSP
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
AGC
DSP
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
AGC
DSP
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
AGC
DSP
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
AGC
DSP
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
AGC
DSP
Professor A G Constantinides© 8
Digital Signal Processing &
Digital Filters
6) Applications
 Communications
 Biomedical
 Seismic
 Audio/Music
AGC
DSP
Professor A G Constantinides© 9
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
AGC
DSP
Professor A G Constantinides© 10
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?
AGC
DSP
Professor A G Constantinides© 11
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?
AGC
DSP
Professor A G Constantinides© 12
Course content
Assumed DSP background
DSP Background folder
 1-Introduction
 2-z transform
 3-transfer functions
 4-Signal Flow Graphs
 5-digital filters intro
AGC
DSP
Professor A G Constantinides© 13
Course content
2-Digital Filter Design
 1-Digital Filters (FIR)
 2-Digital Filters (IIR)
3-Multirate
1-Interpolation_Decimation
AGC
DSP
Professor A G Constantinides© 14
Course content
4-Tranforms
 1-DFT
 2-DFT_one2two
 3-general transforms
 4-Wavelets
5-Finite Wordlength
 1-Finite Wordlength
AGC
DSP
Professor A G Constantinides© 15
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
AGC
DSP
Professor A G Constantinides© 16
Course content
7-Adaptive Signal Processing
 1-Adaptive Signal Processing
8-Applications
 1-Applications
 2-Applications
AGC
DSP
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
AGC
DSP
Professor A G Constantinides© 18
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
AGC
DSP
Professor A G Constantinides© 19
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.
AGC
DSP
Professor A G Constantinides© 20
DIGITAL FILTERS
Power aspects
 Size
 Dissipation
 DSP chips available as well as ASIC/FPGA
realisations
AGC
DSP
Professor A G Constantinides© 21
Applications
Radar systems & Sonar systems
 Doppler filters.
 Clutter Suppression.
 Matched filters.
 Target tracking.
 Identification
AGC
DSP
Professor A G Constantinides© 22
DIGITAL FILTERS
Image Processing
 Image data compression.
 Image filtering.
 Image enhancement.
 Spectral Analysis.
 Scene Analysis / Pattern recognition.
AGC
DSP
Professor A G Constantinides© 23
DIGITAL FILTERS
Biomedical Signal Analysis
 Spatial image enhancement. (X-rays)
 Spectral Analysis.
 3-D reconstruction from projections.
 Digital filtering and Data compression.
AGC
DSP
Professor A G Constantinides© 24
DIGITAL FILTERS
Music
 Music recording.
 Multi-track “mixing”.
 CD and DAT.
 Filtering / Synthesis / Special effects.
AGC
DSP
Professor A G Constantinides© 25
DIGITAL FILTERS
Seismic Signal Analysis
 Bandpass Filtering for S/N
improvement.
 Predictive deconvolution to extract
reverberation characteristics.
 Optimal filtering. (Wiener and Kalman.)
AGC
DSP
Professor A G Constantinides© 26
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

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DSP_Course_Contents.ppt

  • 1. AGC DSP Professor A G Constantinides© 1 Digital Signal Processing & Digital Filters An Introductory Course By Professor A G Constantinides MSc, EE4, ISE4, PhD
  • 2. AGC DSP 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
  • 3. AGC DSP 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
  • 4. AGC DSP 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
  • 5. AGC DSP 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
  • 6. AGC DSP 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
  • 7. AGC DSP 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
  • 8. AGC DSP Professor A G Constantinides© 8 Digital Signal Processing & Digital Filters 6) Applications  Communications  Biomedical  Seismic  Audio/Music
  • 9. AGC DSP Professor A G Constantinides© 9 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
  • 10. AGC DSP Professor A G Constantinides© 10 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?
  • 11. AGC DSP Professor A G Constantinides© 11 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?
  • 12. AGC DSP Professor A G Constantinides© 12 Course content Assumed DSP background DSP Background folder  1-Introduction  2-z transform  3-transfer functions  4-Signal Flow Graphs  5-digital filters intro
  • 13. AGC DSP Professor A G Constantinides© 13 Course content 2-Digital Filter Design  1-Digital Filters (FIR)  2-Digital Filters (IIR) 3-Multirate 1-Interpolation_Decimation
  • 14. AGC DSP Professor A G Constantinides© 14 Course content 4-Tranforms  1-DFT  2-DFT_one2two  3-general transforms  4-Wavelets 5-Finite Wordlength  1-Finite Wordlength
  • 15. AGC DSP Professor A G Constantinides© 15 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
  • 16. AGC DSP Professor A G Constantinides© 16 Course content 7-Adaptive Signal Processing  1-Adaptive Signal Processing 8-Applications  1-Applications  2-Applications
  • 17. AGC DSP 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
  • 18. AGC DSP Professor A G Constantinides© 18 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
  • 19. AGC DSP Professor A G Constantinides© 19 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.
  • 20. AGC DSP Professor A G Constantinides© 20 DIGITAL FILTERS Power aspects  Size  Dissipation  DSP chips available as well as ASIC/FPGA realisations
  • 21. AGC DSP Professor A G Constantinides© 21 Applications Radar systems & Sonar systems  Doppler filters.  Clutter Suppression.  Matched filters.  Target tracking.  Identification
  • 22. AGC DSP Professor A G Constantinides© 22 DIGITAL FILTERS Image Processing  Image data compression.  Image filtering.  Image enhancement.  Spectral Analysis.  Scene Analysis / Pattern recognition.
  • 23. AGC DSP Professor A G Constantinides© 23 DIGITAL FILTERS Biomedical Signal Analysis  Spatial image enhancement. (X-rays)  Spectral Analysis.  3-D reconstruction from projections.  Digital filtering and Data compression.
  • 24. AGC DSP Professor A G Constantinides© 24 DIGITAL FILTERS Music  Music recording.  Multi-track “mixing”.  CD and DAT.  Filtering / Synthesis / Special effects.
  • 25. AGC DSP Professor A G Constantinides© 25 DIGITAL FILTERS Seismic Signal Analysis  Bandpass Filtering for S/N improvement.  Predictive deconvolution to extract reverberation characteristics.  Optimal filtering. (Wiener and Kalman.)
  • 26. AGC DSP Professor A G Constantinides© 26 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