A robust subband adaptive filter algorithm for sparse and block-sparse systems identification

摘要

This paper presents a new subband adaptive filter(SAF)algorithm for system identification scenario under impulsive interference,named generalized continuous mixed p-norm SAF(GCMPN-SAF)algorithm.The proposed algorithm uses a GCMPN cost function to combat the impul-sive interference.To further accelerate the convergence rate in the sparse and the block-sparse system identification processes,the proportionate versions of the proposed algorithm,the L0-norm GCMPN-SAF(L0-GCMPN-SAF)and the block-sparse GCMPN-SAF(BSGCMPN-SAF)algorithms are also developed.Moreover,the convergence analysis of the proposed algorithm is provided.Simulation results show that the proposed algorithms have a better performance than some other state-of-the-art algorithms in the literature with respect to the convergence rate and the tracking capability.