Active noise control is an expanding field that requires a suitable synthesis of secondary perturbations. Unfortunately, most schemes for noise cancelling do not take into account that the input signal that drives the adaptive filter can be noisy. In this Letter, it is theoretically shown that noise perturbations in the excitation data degrade the performance of the standard filtered-x least mean squares (FX-LMS) algorithm. Furthermore, a method that compensates such an issue is devised, and a first-order stochastic analysis of the resulting algorithm is performed. The results reveal that the proposed scheme outperforms the standard FX-LMS algorithm, even when the variance of the additive noise in the input is not accurately estimated.

中文翻译：

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偏置补偿的FX-LMS算法

有源噪声控制是一个不断扩展的领域，需要适当地综合二次扰动。不幸的是，大多数消除噪声的方案没有考虑到驱动自适应滤波器的输入信号可能会产生噪声。在这封信中，从理论上表明，激励数据中的噪声扰动会降低标准滤波x最小均方（FX-LMS）算法的性能。此外，设计了一种补偿这种问题的方法，并对所得算法进行一阶随机分析。结果表明，即使未精确估计输入中附加噪声的方差，该方案也优于标准FX-LMS算法。