A New Subband Adaptive Filtering Algorithm for Sparse System Identification with Impulsive Noise. (20th May 2014) - Choi, Young-Seok
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 l 1 -norm optimization and l 0 -norm penalty of the weight vector in the cost function, the proposed l 0 -norm sign SAF (l 0 -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 l 0 -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.