Maximum Versoria Criterion Algorithm with Adaptive Radius in Active Impulse Noise Control

Abstract

The conventional algorithm used in active noise control (ANC) performs poorly under non-Gaussian (impulse) noise. This is because the stability of a conventional adaptive controller is easily damaged by the impulse noise. For the purpose of eliminating the noise and enhancing stability, two improvements are listed in the paper. Firstly, based on the robustness of the Versoria function to impulsive noise, a filtered-x recursive maximum Versoria criterion (FXRMVC) algorithm is proposed to attenuate the impulsive noise. Secondly, the FXRMVC algorithm employs an adaptive radius strategy which is only subject to the estimated error signal. The strategy can adjust the radius of Versoria function online. The benefit of this method is that the FXRMVC with adaptive radius algorithm breaks step size limitation and avoids noise prior information. The computer simulation results manifest that the proposed algorithm has superior noise reduction, faster convergence rate, lower minimum steady state error and better power spectral density compared with other algorithms in different noise environments.