Dynamic RLS-DCD for Sparse System Identification

Qing Xia; Yun Lin; Hui Luo

doi:10.4028/www.scientific.net/AMM.602-605.2411

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 602-605Dynamic RLS-DCD for Sparse System Identification

Dynamic RLS-DCD for Sparse System Identification

Abstract:

In this passage we propose a computationally efficient adaptive filtering algorithm for sparse system identification.The algorithm is based on dichotomous coordinate descent iterations, reweighting iterations,iterative support detection.In order to reduce the complexity we try to discuss in the support.we suppose the support is partial,and partly erroneous.Then we can use the iterative support detection to solve the problem.Numerical examples show that the proposed method achieves an identification performance better than that of advanced sparse adaptive filters (l1-RLS,l0-RLS) and its performance is close to the oracle performance.

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Periodical:

Applied Mechanics and Materials (Volumes 602-605)

Pages:

2411-2414

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.602-605.2411

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Online since:

August 2014

Authors:

Qing Xia*, Yun Lin, Hui Luo

Keywords:

Iterative Support Detection (ISD), l1-DCD, Prior Information, Reweighting Scheme, Sparse Recovery

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