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摘要
This paper presents a novel subband adaptive filter (SAF) for systemidentificationwhere 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.
- 出版日期2014
