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A robust evolutionary feedforward active noise control system using Wilcoxon norm and particle swarm optimization algorithm

机译:基于Wilcoxon准则和粒子群算法的鲁棒进化前馈主动噪声控制系统

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摘要

The conventional filtered-x least mean square (FxLMS) algorithm commonly employed for active noise control (ANC) is sensitive to disturbances acquired by the error microphone and yields poor performance in such scenario. To circumvent this problem, in this paper, a Wilcoxon FxLMS (WFxLMS) algorithm is proposed and used in the design of an efficient ANC which is robust to outliers in the secondary path and immune to burst noise acquired by the error microphone. It is demonstrated through simulation study that under such situation the proposed algorithm outperforms the traditional FxLMS algorithm. A particle swarm optimization (PSO) algorithm based robust ANC system, which does not require the modeling of the secondary path is also derived in the paper. Improved performance of the robust evolutionary ANC system over L2 norm based evolutionary ANC system is also shown.
机译:通常用于主动噪声控制(ANC)的常规滤波x最小均方(FxLMS)算法对误差麦克风所获取的干扰敏感,并且在这种情况下产生较差的性能。为了解决这个问题,在本文中,提出了一种Wilcoxon FxLMS(WFxLMS)算法,并将其用于有效的ANC设计中,该ANC对次级路径中的异常值具有鲁棒性,并且对误差麦克风获得的突发噪声具有免疫力。通过仿真研究表明,在这种情况下,所提算法优于传统的FxLMS算法。本文还提出了一种基于粒子群优化(PSO)算法的鲁棒ANC系统,该算法不需要对次级路径进行建模。还示出了基于基于L2范数的进化ANC系统的鲁棒进化ANC系统的改进性能。

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