Projection FxLMS framework of active noise control against impulsive noise environments

Abstract

This paper focuses on active noise control in the presence of disturbance from an α-stable distribution. The filtered-x fractional lower-order covariance algorithm has been introduced to enhance the performance of traditional algorithms in impulsive noise environments. For minimal adjustment of the weight vector, another filtered-x normalized fractional lower-order covariance (FxNFLOC) algorithm is proposed. Furthermore, the projection approach of the filtered-x least mean square (FxLMS) algorithm is explored. Within this framework, a new algorithm called filtered-x least mean logarithmic square (FxLMLS), which employs a logarithmic function, is devised. The convergence conditions of the developed schemes are also derived. Numerical examples demonstrate the effectiveness and superior performance of the FxNFLOC and FxLMLS algorithms in handling impulsive noise over existing competitors in various scenarios.