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Journal of Applied Mathematics
Volume 2014 (2014), Article ID 704231, 7 pages
Research Article

A New Subband Adaptive Filtering Algorithm for Sparse System Identification with Impulsive Noise

Department of Electronic Engineering, Gangneung-Wonju National University, Gangneung 210-702, Republic of Korea

Received 13 March 2014; Revised 21 April 2014; Accepted 5 May 2014; Published 20 May 2014

Academic Editor: Guiming Luo

Copyright © 2014 Young-Seok Choi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a novel subband adaptive filter (SAF) for system identification where an impulse response is sparse and disturbed with an impulsive noise. Benefiting from the uses of -norm optimization and -norm penalty of the weight vector in the cost function, the proposed -norm sign SAF ( -SSAF) achieves both robustness against impulsive noise and remarkably improved convergence behavior more than the classical adaptive filters. Simulation results in the system identification scenario confirm that the proposed -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.