EECS 559: Advanced Signal Processing

University of Michigan, Fall 2006

Instructor: Clayton Scott
Classroom: 3433 EECS
Time: MW 10:30-12
Office: 4229 EECS
Email:
Office hours: Friday 10:30-12

Announcements:

Textbook: Steven Kay, Modern Spectral Estimation, Prentice Hall

Topics: Spectral estimation (most of course) and pattern recognition (time permitting).

Prerequisites:
Digital signal processing: LTI systems, filtering, Fourier and z-transforms
Linear algebra: eigenvalues/vectors, solving linear systems, least squares problems, projections
Probability: Random variables, expectation, correlation. Familiarity with random processes and statistical estimation a plus.

Relevant papers, available on IEEE Xplore. To access Proc. IEEE, follow Journals and Magazines -> P -> Proceedings of the IEEE.

  1. Kay and Marple, Spectrum analysis--A modern perspective, Proc. IEEE, vol. 69, no. 11, 1380-1419, 1981.
  2. Robinson, A historical perspective of spectrum estimation, Proc. IEEE, vol. 70, no. 9, 885-907, 1982.
  3. Johnson, The application of spectral estimation methods to bearing estimation problems, Proc. IEEE, vol. 70, no. 9, 1018-1028, 1982.

Lecture notes:

  1. Overview
  2. Random processes
  3. The Power Spectral Density
  4. The Periodogram
  5. Classical (Nonparametric) Spectrum Estimation
  6. Parametric Modeling: ARMA Models
  7. AR Spectral Estimation in Theory (connections to linear prediction)
  8. AR Spectral Estimation in Practice
  9. MA and ARMA Spectral Estimation
  10. Capon's Method
  11. Sinusoidal Parametric Modeling
  12. Bearing Estimation
  13. Classification
  14. Plug-In Rules; LDA and QDA
  15. EM Algorithm for Gaussian Mixture Models
  16. Kernel classifiers
  17. Linear classifiers
  18. Constrained Optimization
  19. Support vector machines
  20. Boosting and other voting methods

Homeworks:

  1. Homework 1, Due 9/13.
  2. Homework 2, Due 9/20. Solutions
  3. Homework 3, Due 9/27.
  4. Homework 4, Due 10/4. Solutions
  5. Homework 5, Due 10/11. Solutions
  6. Homework 6, Due 10/25. Solutions
  7. Homework 7, Due 11/1.
  8. Homework 8, Due 11/20.
  9. Homework 9, Due 11/29.
  10. Homework 10, Due 12/13.

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