Pairwise Optimal Weight Realization-Acceleration Technique for Set-Theoretic Adaptive Parallel Subgradient Projection Algorithm

The adaptive parallel subgradient projection (PSP) algorithm was proposed in 2002 as a set-theoretic adaptive filtering algorithm providing fast and stable convergence, robustness against noise, and low computational complexity by using weighted parallel projections onto multiple time-varying closed...

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Vydáno v:	IEEE transactions on signal processing Ročník 54; číslo 12; s. 4557 - 4571
Hlavní autoři:	Yukawa, M., Yamada, I.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York, NY IEEE 01.12.2006 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Acceleration Adaptive algorithms Adaptive filters Adaptive parallel subgradient projection Algorithms Applied sciences Computational complexity Convergence Detection, estimation, filtering, equalization, prediction Exact sciences and technology Filtering algorithms Half spaces Information, signal and communications theory Least squares methods Mathematical analysis Mathematical models optimal weight design Optimization Projection Projection algorithms Resonance light scattering set-theoretic adaptive filtering Signal and communications theory Signal processing algorithms Signal, noise Studies Telecommunications and information theory Transversal filters Parallel algorithm optimal weight design Adaptive algorithm Adaptive filtering Parallel architectures Affine transformation Recursive algorithm Computational complexity Half space Time variation Adaptive parallel subgradient projection set-theoretic adaptive filtering Optimal design Fast filter Weighting Least squares method Transverse filter Convergence rate Noise immunity Numerical simulation Set theory Fast algorithm Newton method
ISSN:	1053-587X, 1941-0476
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Popis
Shrnutí:	The adaptive parallel subgradient projection (PSP) algorithm was proposed in 2002 as a set-theoretic adaptive filtering algorithm providing fast and stable convergence, robustness against noise, and low computational complexity by using weighted parallel projections onto multiple time-varying closed half-spaces. In this paper, we present a novel weighting technique named pairwise optimal weight realization (POWER) for further acceleration of the adaptive PSP algorithm. A simple closed-form formula is derived to compute the projection onto the intersection of two closed half-spaces defined by a triplet of vectors. Using the formula inductively, the proposed weighting technique realizes a good direction of update. The resulting weights turn out to be pairwise optimal in a certain sense. The proposed algorithm has the inherently parallel structure composed of q primitive functions, hence its total computational complexity O(qrN) is reduced to O(rN) with q concurrent processors (r: a constant positive integer). Numerical examples demonstrate that the proposed technique for r=1 yields significantly faster convergence than not only adaptive PSP with uniform weights, affine projection algorithm, and fast Newton transversal filters but also the regularized recursive least squares algorithm
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23
ISSN:	1053-587X 1941-0476
DOI:	10.1109/TSP.2006.881225