Announcements

- Solutions for Homeworks 7 and 8 have been posted to bSpace. Self-graded scores for Homework 7 are due by noon on Monday.
- Homework 7 update: Submit problems 1 - 4 in class on Thursday. Problems 5 - 9 can be submitted to Lea Barker in 253 Cory until 4 PM on Friday.
- Midterm 2 will be held on Thursday, May 6, at 7 -- 9 PM, in 247 Cory
- Homework 8 has been posted
- Homework 7 and Homework 6 solutions have been posted

Administrative Info

Instructor: Professor Kannan
Ramchandran, 269 Cory Hall, |

Lectures: Tuesday and Thursday, 9:30 - 11:00 am, 293
Cory |

Office hours: Tuesday, 11:00 am - 12:00 pm, 258 Cory
Hall |

GSI: None |

Point of Contact: Mark Johnson, |

Course Administrative Assistant: Lea
Barker, 253 Cory Hall, |

Course website: http://inst.eecs.berkeley.edu/~ee225a/sp10 |

Course Info

**Description**

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.

EE 123, EE 126, and familiarity with linear algebra; or equivalent; or consent of instructor.

There will be bi-weekly homework assignments (15% of course grade), a Midterm Exam (40%), and a Final Exam (45%).

- Monson H. Hayes,
*Statistical Digital Signal Processing and Modeling*, Wiley, 1996. (ISBN 0471594318) [ Matlab files ] [ Errata ]

- Overview and Background: vector spaces, allpass, minimum-phase, maximum-phase, linear-phase filters, Z-transforms and properties, sampling.
- Multirate DSP: filter banks, wavelets, time-frequency analysis
- Transforms, KLT, quantization, sparse signal representation, compressed sensing
- Array processing
- Spectral estimation: MMSE estimation, Wiener filtering, orthogonality principle
- Adaptive filtering, linear prediction, LMS, convergence analysis, RLS
- Applications of adaptive filtering algorithms

Handouts

- SP Magazine article on sampling sparse signals
- Notes on Parametric Spectral Estimation
- Supplementary Notes from Prof. Ed Lee

Homework (Solutions will be posted on bSpace)

The detailed homework grading and submission policy can be downloaded here. Please familiarize yourself with the homework submission policy and the department policy on academic dishonesty.

- Homework 8
- Homework 7
- Homework 6
- Homework 5 [y.mat] [y1.mat] [y2.mat]
- Homework 4
- Homework 3
- Homework 2
- Homework 1

Resources

The following books may be useful. Those marked Reserved are on reserve at the Kresge Engineering Library.

- 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, 4th edition, Prentice-Hall, 2007 Reserved
- J.S. Lim and A. V. Oppenheim, Eds, Advanced Topics in Signal Processing, Prentice-Hall, 1988
- S. K. Mitra, Digital Signal Processing: A Computer-Based Approach, McGraw Hill, 1998

- M. Vetterli and J. Kovacevic, Wavelets and Subband Coding, Prentice-Hall, 1995 Reserved [ Online version ]
- G. Strand and T. Nguyen, Wavelets and Filter Banks, Wellesley, 1997 Reserved
- P. P. Vaidyanathan, Multirate Systems and Filter Banks, Prentice-Hall, 1993
- S. Mallat, A Wavelet Tour of Signal Processing, Academic Press, 1998.

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

- 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.

- P. Stoica and R. Moses, Introduction to Spectral Analysis, Prentice-Hall, 1997
- S. M. Kay, Modern Spectral Estimation, Theory and Applications, Prentice-Hall, 1988

- S. Haykin, Adaptive Filter Theory, 4th Ed., Prentice-Hall, 2002 Reserved
- P.M. Clarkson, Optimal and Adaptive Signal Processing, CRC Press, 1993
- B. Widrow and S. D. Stearns, Adaptive Signal Processing, Prentice-Hall, 1985

- R. Blahut, Fast Algorithms for Digital Signal Processing, Addison-Wesley, 1984

- 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