Bias-Compensated Normalized Least-Mean Fourth Algorithm for Noisy Input

Abstract

This paper proposes a bias-compensated normalized least-mean fourth (NLMF) algorithm to compensate for the bias caused by noisy input. In the proposed algorithm, we add a bias-compensation vector to the conventional NLMF algorithm, and the bias-compensation vector is then derived based on the unbiasedness criterion. Simulation results in system identification context show that the proposed algorithm provides lower steady-state misalignment as compared to the conventional NLMF algorithm.