A novel normalized sign algorithm for system identification under impulsive noise interference

To overcome the performance degradation of adaptive filtering algorithm in presence of impulsive noise, a novel normalized sign algorithm (NSA) based on the convex combination strategy is proposed in this paper, which is an adaptive combination of two NSA filters with the different step-size, called NSA-NSA. The proposed approach is capable of solving the conflicting requirement of fast convergence rate and low steady-state error for the single NSA filter. To further improve the robustness against impulsive noise, a mixing parameter updating formula based on a sign cost function is derived. Moreover, a tracking weight transfer scheme of coefficients from a fast NSA filter to a slow NSA filter is proposed for speed up convergence rate. Finally, the proposed algorithm is verified by theoretical analysis and simulation studies.