A novel subband adaptive filter algorithm against impulsive noise and it's performance analysis

The main drawback of the sign subband adaptive filter algorithm (SSAF) is its large steady-state error. To improve the performance, this paper proposes a novel normalized logarithmic subband adaptive filter algorithm (NLSAF), which is derived from a new normalized logarithmic cost function. Due to possess the advantages of the normalized subband adaptive filter (NSAF) and SSAF algorithms in the proposed NLSAF algorithm, it achieves a low steady-state error and the robustness performance against impulsive noise. Then, by using the energy conservation method, the mean-square convergence performance of the proposed NLSAF algorithm is presented. Simulations on system identifications demonstrate that the proposed subband adaptive filter performs better than the conventional SSAF algorithm in an impulsive-noise scenario.