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....
View Full Document
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.
- Spring '08
- Signal Processing