Variable Step Size for Improving Convergence of FxLMS Algorithm

Abstract Several approaches have been introduced for active noise control (ANC) systems. The most popular adaptation algorithm used for Active Noise Control(ANC) applications is the Filtered-x Least Mean Square (FxLMS) algorithm. In this paper, FxLMS algorithm with variable step size to improve the convergence of ANC system has been proposed. This algorithm is mostly preferred, because it used as controller in adaptation filter to update the filter coefficients. This new algorithm is based onarc-tangent function and it will improve the convergence as well as a reduction in noise compared with conventional FxLMS. The convergence and noise reduction rate are analyzed with the help of MATLAB. Simulation results show that the convergence speed and noise reduction of the variable step algorithm are superior to conventional FxLMS algorithm.