EE 225A Spring 2007

Resources

Instructions: Lecture scribe notes are written up in LaTeX using the LaTeX template (see the corresponding PDF file). Scribe notes are due no later than 4 days after the lecture, via e-mail to the instructor. Please use, as your e-mail subject line, [EE 225A] Lecture Scribe #N, where N is the lecture number, according to the schedule. The notes will be reviewed, and necessary editing/corrections will be indicated.

Computational aspects of covariance and autocorrelation matrices. M. Morf, et al, Efficient solution of covariance equations for linear prediction. IEEE Transactions on Acoustics, Speech and Signal Processing, vol 25, no 5, October 1977. An excellent resource is also the book by Golub and van Loan, Matrix Computations.
Minimum description length principle. A. Barron, J. Rissanen, B. Yu, The minimum description length principle in coding and modeling. IEEE Transactions on Information Theory, vol 44, no 6, October 1998.
Frequency estimation. Here, there are many more techniques that we did not discuss in class, such as the MUSIC algorithm. The original paper is R. Schmidt, Multiple emitter location and signal parameter estimation. Proceedings of the RADC Spectrum Estimation Workshop, pp. 243-258, 1979. (The link is to a journal version of this work.)
Sampling signals with finite rate of innovation. M. Vetterli, T. Blu, P. Marziliano, Sampling signals with finite rate of innovation. IEEE Transactions on Signal Processing, vol 50, no 6, June 2002.
Transform Coding: V. Goyal, Theoretical foundations of transform coding. IEEE Signal Processing Magazine, vol 18, no 5, Sept. 2001. This is a nicely written overview++ paper of transform coding.
Applications of Graphical Models in Signal Processing

Project proposals: Proposals should include a paragraph on background, a paragraph on what the author plans on achieving, and a list of references (at least three). Please use the following LaTex template (which also serves as an example project proposal) and the corresponding PDF file.
Final Reports: The final reports are due in LaTeX format and will be pasted together into a book of Project Proceedings which will be distributed to all students in the class. Each project corresponds to one chapter of the book. Please use the following LaTex template for your chapter. Rename the file into "chYourName.tex", where you replace "YourName" by your actual name. If you want to compile your chapter, you'll need the main LaTeX file, and the following class file. Put all three files into the same directory, and change the line "\include{chGastpar}" in the main LaTeX file to "\include{chYourName}". And here is what the final product will look like.

Linear Algebra
- G. Strang, Linear Algebra and Applications, Academic Press, 1980.
- Horn and Johnson, Matrix Analysis. Cambridge University Press, 1985.
General DSP
- A. Oppenheim and R. Schafer with J. Buck, Discrete-time Signal Processing. Second Edition. Prentice-Hall, 1999 [Reserved].
- J. Proakis and D. Manolakis, Digital Signal Processing: Principles, Algorithms, and Applications. Third edition. Prentice-Hall, 1996. [Reserved]
- S. K. Mitra, Digital Signal Processing: A Computer-Based Approach. McGraw Hill, 1998.
- P. Bremaud. Mathematical principles of signal processing: Fourier and Wavelet analysis. Springer, 2002. [Reserved]
Adaptive Filtering
- P. M. Clarkson, Optimal and Adaptive Signal Processing. CRC Press, Boca Raton, FL, 1993.
- B. Widrow and S. D. Stearns, Adaptive Signal Processing. Prentice-Hall, 1985.
- S. Haykin, Adaptive Filter Theory. Second Edition. Prentice-Hall, 1991. [Reserved]
Statistical Signal Processing
- B. Porat, Digital Processing of Random Signals: theory and methods. Prentice-Hall, 1994. [Reserved]
- M. Hayes, Statistical Digital Signal Processing and Modeling. Prentice-Hall, 1996. [Reserved]
Wavelets and multi-rate
- M. Vetterli and J. Kovacevic. Wavelets and Subband Coding. Prentice-Hall: Upper Saddle River, NJ, 1993.
- S. Mallat. A Wavelet Tour of Signal Processing. Second Edition. Academic Press: London, 1999.
Further Topics: See Course Information Leaflet

The class web sites of previous offerings of this course at Berkeley include much useful material: Spring 2000; Spring 2001; Spring 2003; Spring 2005; Spring 2006

Several online encyclopedic resources are excellent sources of mathematical definitions and concepts:

If you are looking for additional background on complex variable theory, a tutorial on complex variable theory by Dan Sloughter is recommended.