A Robust Fully Arctangent Adaptive Interpolated Volterra Filtering Algorithm Against Impulsive Noise

Abstract

The applicability of adaptive Volterra filter is greatly limited by the high computational complexity and notable performance degradation when encountering the impulsive noise. Although the existing interpolated adaptive Volterra filter has reduced the computational complexity, its performance is still significantly degraded while the impulsive noise occurs. This brief proposes a robust fully arctangent adaptive fully interpolated Volterra (RFAAFIV) filtering algorithm by using the novel arctangent function. The proposed algorithm can effectively improve the robustness against impulsive noise while requiring the low computational cost. Moreover, the computational complexity and the steady-state mean square performance of the proposed RFAAFIV algorithm are analyzed. Simulations on nonlinear system identification further evaluate the effectiveness of the RFAAFIV algorithm against impulsive noise and verify the theoretical analysis.