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