Sparsity Regularized Affine Projection Adaptive Filtering for System Identification

Young-Seok CHOI  

IEICE TRANSACTIONS on Information and Systems   Vol.E97-D   No.4   pp.964-967
Publication Date: 2014/04/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E97.D.964
Type of Manuscript: LETTER
Category: Fundamentals of Information Systems
system identification,  adaptive filter,  affine projection,  sparsity,  sparse system,  

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A new type of the affine projection (AP) algorithms which incorporates the sparsity condition of a system is presented. To exploit the sparsity of the system, a weighted l1-norm regularization is imposed on the cost function of the AP algorithm. Minimizing the cost function with a subgradient calculus and choosing two distinct weightings for l1-norm, two stochastic gradient based sparsity regularized AP (SR-AP) algorithms are developed. Experimental results show that the SR-AP algorithms outperform the typical AP counterparts for identifying sparse systems.