## Instructor:Kannan Ramchandran269 Cory Hall kannanr@eecs.berkeley.edu |
## Office hours:Tuesdays 11 - 12258 Cory Hall |

## Lecture hours:Tuesdays and Thursdays9:30 - 11 35 Evans |
## Online resources:http://www-inst.eecs.berkeley.edu/~ee225aucb.class.ee225a |

- Monday 01/26/09, 521 Cory Hall, 6pm-7pm. (DSP background review)

- There will be no lectures on Tuesday 02/10

- HW's: 15%
- Midterm: 40%
- Final: 45%

- Monson H. Hayes, Statistical Digital Signal Processing and Modeling, Wiley, 1996 (ISBN 0471594318)

- Nebojsa Milosavljevic, 264 Cory Hall, nebojsa@eecs.berkeley.edu

- Amber Morales, 253 Cory Hall, morales@eecs.berkeley.edu

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.

- 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

- 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.

- 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

- B. Porat, Digital Processing of Random Signals: theory and methods, Prentice-Hall, 1994.
- Monson Hayes, Stochastic Signal Processing, Prentice-Hall, 1996. Reserved

- 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

- 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.

- 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.

- R. Blahut, Fast algorithms for digital signal processing, Reading, MA, Addison-Wesley, 1984. Reserved

- A. Papoulis, Probability, Random Variables and Stochastic Processes, McGraw-Hill, 1984.
- A. Leon-Garcia, Probability and Random Processes for Electrical Engineering, Addison-Wesley, 1993.

- Gilbert Strang, Linear Algebra and Applications, Academic Press, 1980. Reserved

- 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]

The detailed homework submission policy can be downloaded or printed here [ link]. Familiarize yourself with the homework submission and grading policy.