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

Young-Seok Choi

Journal of Applied Mathematics, 2014, vol. 2014, 1-7

Abstract:

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.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnljam:704231

DOI: 10.1155/2014/704231

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