Text: Adaptive Filter Theory by S. Haykin, Prentice Hall - 3rd Edition - 1996

Prerequisites: EEE407 and EEE350

Objective: The goal of this course is to introduce graduate students to the principles and applications of adaptive signal processing.

Outline:

The course will cover selected topics from the book and from research papers: adaptive linear combiner, Mean square error, Wiener least-squares solution, Autocorrelation matrices, eigenvalues - eigenvectors and geometrical interpretation, Gradient search and performance surfaces, The LMS and the RLS algorithms, Block time and frequency domain LMS FIR and IIR adaptive filters, The Equation error model, Selected algorithms and applications from recent papers.
 

Course Coordinator: Andreas Spanias

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