Design and Analysis of Robust Adaptive Filtering with the Hyperbolic Tangent Exponential Kernel M-Estimator Function for Active Noise Control

Abstract--In this work, we propose a robust adaptive filtering approach for active noise control applications in the prese nce of impulsive noise. In particular, we develop the filtered-x hyperbolic tangent exponential generalized Kernel M-esti mate function (FXHEKM) robust adaptive algorithm. A statistica l analysis of the proposed FXHEKM algorithm is carried out alo ng with a study of its computational cost. In order to evaluate t he proposed FXHEKM algorithm, the mean-square error (MSE) and the average noise reduction (ANR) performance metrics have been adopted. Numerical results show the efficiency of the proposed FXHEKM algorithm to cancel the presence of the additive spurious signals, such as α-stable noises against competing algorithms. Signal processing applications suffer from the effects of undesired acoustic signals, known as noise, which come from different sources and heavily degrade the general operatio n of digital signal processing systems.