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

Young-Seok Choi

Journal of Applied Mathematics, 2014, vol. 2014, issue 1

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 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 remarkably improved convergence behavior more 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.

Date: 2014
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https://doi.org/10.1155/2014/704231

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Persistent link: https://EconPapers.repec.org/RePEc:wly:jnljam:v:2014:y:2014:i:1:n:704231

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