%0 Journal Article
	%A Young-Seok Choi
	%D 2016
	%J International Journal of Electrical and Computer Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 109, 2016
	%T Subband Adaptive Filter Exploiting Sparsity of System
	%U https://publications.waset.org/pdf/10003839
	%V 109
	%X This paper presents a normalized subband adaptive
filtering (NSAF) algorithm to cope with the sparsity condition of
an underlying system in the context of compressive sensing. By
regularizing a weighted l1-norm of the filter taps estimate onto the
cost function of the NSAF and utilizing a subgradient analysis,
the update recursion of the l1-norm constraint NSAF is derived.
Considering two distinct weighted l1-norm regularization cases, two
versions of the l1-norm constraint NSAF are presented. Simulation
results clearly indicate the superior performance of the proposed
l1-norm constraint NSAFs comparing with the classical NSAF.
	%P 125 - 128