Technical Program

Paper Detail

Paper:SPTM-P11.6
Session:Filter Banks and Subband Coding
Time:Friday, May 21, 09:30 - 11:30
Presentation: Poster
Topic: Signal Processing Theory and Methods: Multi-rate Signal Processing & Wavelets
Title: ITERATIVE GRADIENT TECHNIQUE FOR THE DESIGN OF LEAST SQUARES OPTIMAL FIR MAGNITUDE SQUARED NYQUIST FILTERS
Authors: Andre Tkacenko; California Institute of Technology 
 Palghat P. Vaidyanathan; California Institute of Technology 
Abstract: Recently, much attention has been given to the design of optimal finite impulse response (FIR) compaction filters. Such filters, which arise in the design of optimal signal-adapted orthonormal FIR filter banks, satisfy a magnitude squared Nyquist constraint in addition to the inherent FIR assumption. In this paper, we focus on the least squares optimal design of FIR filters whose magnitude squared response satisfies a Nyquist constraint. Using a complete characterization of such systems in terms of Householder-like building blocks, an iterative gradient based greedy algorithm is proposed to design such filters. Simulation results provided show the merit of the proposed technique for designing FIR compaction filters.
 
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