SDP design procedures for near-optimum IIR compaction filters
Signal Processing
Efficient state-space approach for FIR filter bank completion
Signal Processing
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We propose a new technique for finding the optimum FIR compaction filter adapted to signal statistics. The main novelty of our approach is the transformation of the original problem into the maximum eigenvalue minimization of a parameterized Toeplitz matrix, with only O(N) variables. This is a typical application of semidefinite programming (SDP) and may be solved with reliable interior-point algorithms. Our algorithm is to be compared with the method of Tuqan and Vaidyanathan (1998), which has O(N/sup 2/) variables. The numerical experiments show that the optimum compaction filter is obtained with good numerical accuracy and convenient execution time for filters of order up to 100.