Abstract: In order to improve the filtering performance of the normalized subband adaptive filter (NSAF) in a non-Gaussian noise environment, the maximum mixture correntropy criterion and fractional-order differentiation are applied to the NSAF algorithm in this paper. On the one hand, the robustness of the maximum mixture correntropy criterion is used to effectively suppress the effect of anomalous noise values on the performance of the algorithm. On the other hand, to describe the actual system more accurately, a fractional-order differentiation component is added to the weight update. The proposed algorithm is applied to system identification and nonlinear channel equalization in a non-Gaussian impact noise and colored noise environment. Simulation results show that the proposed algorithm has stronger robustness and better system tracking and estimation capability compared with existing robust algorithms.

Key words: subband adaptive filtering algorithm, mixture correntropy Criterion, fractional-order derivative, non-Gaussian impulsive interference, system identification