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# DSP_Course_Contents.ppt

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# DSP_Course_Contents.ppt

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### DSP_Course_Contents.ppt

1. 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. 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. 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. 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. 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. 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. 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. 8. AGC DSP Professor A G Constantinides© 8 Digital Signal Processing & Digital Filters 6) Applications  Communications  Biomedical  Seismic  Audio/Music
9. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 20. AGC DSP Professor A G Constantinides© 20 DIGITAL FILTERS Power aspects  Size  Dissipation  DSP chips available as well as ASIC/FPGA realisations
21. 21. AGC DSP Professor A G Constantinides© 21 Applications Radar systems & Sonar systems  Doppler filters.  Clutter Suppression.  Matched filters.  Target tracking.  Identification
22. 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. 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. 24. AGC DSP Professor A G Constantinides© 24 DIGITAL FILTERS Music  Music recording.  Multi-track “mixing”.  CD and DAT.  Filtering / Synthesis / Special effects.
25. 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. 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