Variable step-size sign subband adaptive filter with subband filter selection

Abstract

Abstract This letter proposes a novel sign subband adaptive filtering (SSAF) algorithm with a subset selection for subband filters, called the SS-SSAF. The proposed algorithm achieves the fast convergence performance and reduces the computational complexity by a proposed sufficient condition. The condition associated with each subband immediately ensures the decrease of the mean square deviation (MSD) value at every iteration. Furthermore, we suggest the variable step-size algorithm for SS-SSAF to achieve both fast convergence speed and small steady-state errors. Simulation results show that the proposed algorithm with fixed step-size performs better than the conventional SSAF and the other improved SSAF algorithms in terms of the convergence rate. In addition, the performance of proposed variable step-size algorithm is demonstrated in the system identification compared with recent variable step-size SSAFs.