| 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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