%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 Sparsity-Aware and Noise-Robust Subband Adaptive Filter
	%U https://publications.waset.org/pdf/10003881
	%V 109
	%X This paper presents a subband adaptive filter (SAF)
for a system identification where an impulse response is sparse
and disturbed with an impulsive noise. Benefiting from the uses
of l1-norm optimization and l0-norm penalty of the weight vector
in the cost function, the proposed l0-norm sign SAF (l0-SSAF)
achieves both robustness against impulsive noise and much improved
convergence behavior than the classical adaptive filters. Simulation
results in the system identification scenario confirm that the proposed
l0-norm SSAF is not only more robust but also faster and more
accurate than its counterparts in the sparse system identification in
the presence of impulsive noise.
	%P 137 - 140