EE225a: Digital Signal Processing
Discussion Sessions:
- Monday 01/26/09, 521 Cory Hall, 6pm-7pm. (DSP background review)
Announcements:
- There will be no lectures on Tuesday 02/10
Grading:
- HW's: 15%
- Midterm: 40%
- Final: 45%
Textbook
- Monson H. Hayes, Statistical Digital Signal Processing and Modeling, Wiley, 1996 (ISBN 0471594318)
Point of Contact:
Administrative Assistant:
Overview
With
signal processing becoming ubiquitous in today's computer literate
world, a large number of application areas are growing in importance,
both in industry and in the research community, such as signal
processing for distributed sensor networks, speech, image and video processing, medical image processing,
wavelets and multiresolution signal processing, genomic and biomedical signal processing, financial data
signal processing, etc. This course will cover some of the theoretical, algorithmic and practical
foundations needed to address this litany of problems and applications in signal processing.
Tentative course schedule:
- Review of vector spaces, allpass, minimum-phase, maximum-phase, linear-phase filters,
Z-transforms and properties, statistical DSP concepts, sampling.
- Multirate DSP: filter banks, wavelets, time-frequency analysis, uncertainty principle
- Stochastic signal models (AR, MA, ARMA)
- Transforms: KLT, wavelet-packets, applications to signal decomposition/compression
- Sparse signal representation, compressed sensing
- Quantization: Quantization theory, rate-distortion theory
- Spectral estimation: MMSE estimation, Wiener filtering, orthogonality principle
- Adaptive filtering, linear prediction, Levinson-Durbin algorithm
- LMS, convergence analysis, fast RLS
- Applications of adaptive filter algorithms: echo-cancellation, system
identification and channel equalization
References for background:
Some textbooks are on reserve in the engineering library.
General DSP:
- A. V. Oppenheim and R. W. Schafer with John R. Buck, Discrete-time Signal
Processing, Second Edition, Prentice-Hall, 1999 Reserved
- J. Proakis and D. Manolakis, Digital Signal Processing: Principles,
Algorithms, and Applications, 3rd edition, Prentice-Hall, 1996.
Reserved
- J.S. Lim and A. V. Oppenheim, Eds, Advanced Topics in Signal Processing,
Prentice-Hall, Englewood Cliffs, NJ, 1988
- S. K. Mitra, Digital Signal Processing: A Computer-Based Approach, McGraw Hill, 1998.
Adaptive filtering:
- P.M. Clarkson, Optimal and Adaptive Signal Processing, CRC Press, Boca
Raton, FL, 1993. Reserved
- B. Widrow and S. D. Stearns, Adaptive Signal Processing, Prentice-Hall,
1985
- S. Haykin, Adaptive Filter Theory, 4th Ed., Prentice-Hall, 2002.
Reserved
Statistical signal processing:
- B. Porat, Digital Processing of Random Signals: theory and methods,
Prentice-Hall, 1994.
- Monson Hayes, Stochastic Signal Processing, Prentice-Hall, 1996.
Reserved
Spectral analysis:
- P. Stoica and R. Moses, Introduction to Spectral Analysis,
Prentice-Hall, Englewood Cliffs, NJ, 1997
- S. M. Kay, Modern Spectral Estimation, Theory and Applications,
Prentice-Hall, Englewood Cliffs, NJ, 1988
Multirate signal processing and wavelets:
- M. Vetterli and J. Kovacevic, Wavelets and subband coding, Prentice-Hall,
1995. Reserved
- P. P. Vaidyanathan, Multirate systems and filter banks, Prentice-Hall,
1993. Reserved
- S. Mallat, A Wavelet Tour of Signal Processing, Academic Press, 1998.
Quantization and coding
- N. Jayant and P. Noll, Digital Coding of Waveforms, Prentice-Hall, 1984
- A. Gersho and R. M. Gray, Vector quantization and signal compression,
Kluwer Academic Publishers, 1992.
Fast algorithms
- R. Blahut, Fast algorithms for digital signal processing, Reading, MA,
Addison-Wesley, 1984. Reserved
Probability
- A. Papoulis, Probability, Random Variables and Stochastic Processes,
McGraw-Hill, 1984.
- A. Leon-Garcia, Probability and Random Processes for Electrical Engineering,
Addison-Wesley, 1993.
Linear algebra
- Gilbert Strang, Linear Algebra and Applications, Academic Press, 1980.
Reserved
Resources
- M. Vetterli and J. Kovacevic, Wavelets and subband coding, Prentice-Hall, 1995. [ link]
- Frequency domain formulation [ link]
- Time domain methods [ link]
- High resolution methods for parametric spectral estimation [ link]
Homeworks (Solutions will be posted on bspace)
The detailed homework submission policy can be downloaded or printed here
[ link].
Familiarize yourself with the homework submission and grading policy.