syllabus - eigendecompositions with on-line algorithms and...

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EEL 6502 ADAPTIVE SIGNAL PROCESSING Spring 2011 Instructor: Jose Principe Office: EB 451 Phone: 352-392-2662 Email [email protected] Class Hours: Tu 2 th -3 th , Th 2 Office Hours: Tu 4 th , Th 3 TextBook : Adaptive Filter Theory, Simon Haykin, Prentice-Hall, 2002, ISBN 013-090126-1 References: Adaptive Signal Processing , Bernie Widrow and Stearns, Prentice Hall, Fundamentals of Adaptive Filtering , Ali Sayed, Wiley, 2003 Kernel Adaptive Filtering , Liu, Principe and Haykin, Wiley 2010 Course Goals : The goal is to present the theory of adaptive signal processing and cover several engineering applications. The major topics will be the concept of adaptation, performance measures and the implementation of adaptive algorithms. Both the LMS and the RLS will be covered in detail. Adaptation of the signal bases will also be covered, such as
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Unformatted text preview: eigendecompositions with on-line algorithms, and adaptation of generalized feedforward filters. Adaptive filtering in reproducing kernel Hilbert Spaces (RKHS) is introduced. Topics: Adaptation as function approximation Filters as Function approximators Wiener Filter Theory Iterative algorithms Theory of adaptation: properties, search, measures Adaptive algorithms LMS RLS Frequency domain LMS Eigendecompositions Whitening transforms Adaptation in signal spaces: Generalized Feedforward Filters Lattice structures Adaptation in RKHS Theory KLMS KRLS Grading: Homework 25% Project I 25% Project II 25% Exam 25% Computer Projects: Several application areas will be outlined. During the course students will have the opportunity to program adaptive algorithms in MATLAB and test them in real world data....
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This note was uploaded on 06/05/2011 for the course EEL 6502 taught by Professor Principe during the Spring '08 term at University of Florida.

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