University of California, Santa Barbara
Department of Electrical and Computer Engineering

Adaptive Filter Theory

ECE 245 - Spring 2011

Instructor: Professor John J. Shynk

Schedule: Tuesday and Thursday
4:00 - 5:50 p.m.
Phelps 1431

 

Announcements:

Office Hours:

Tuesday and Thursday 2:00 - 3:00 p.m.

Course Information:

Theory and analysis of adaptive filters. Optimal filtering, linear prediction, method of least squares.
Steepest-descent and Newton search methods, gradient estimation, LMS adaptive algorithm, recursive least squares.
Gradient and least-squares lattice algorithms for joint-process estimation. Convergence analysis, stability conditions,
time constants, misadjustment.

Grading:

Homework Problems (weekly), 20%
Programming Assignment, 30% (Thursday, June 2, 4:00 p.m.)
Final Exam (open book), 50% (Thursday, June 9, 10:00 - 1:00 p.m.)(NEW TIME)

Required Text:

Haykin, Adaptive Filter Theory, Prentice-Hall, 4th Edition, 2002

Lecture Handouts:

 

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Last Updated: June 7, 2011