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.
Citation
Young-Seok Choi. "A New Subband Adaptive Filtering Algorithm for Sparse System Identification with Impulsive Noise." J. Appl. Math. 2014 (SI11) 1 - 7, 2014. https://doi.org/10.1155/2014/704231
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