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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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- Spring '08
- Signal Processing