Active noise control of impulsive noise with selective outlier elimination

M. Bergamasco, F. D. Rossa, L. Piroddi
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引用次数: 4

Abstract

Traditional active noise control (ANC) methods are based on adaptive filtering algorithms designed to minimize the noise variance. The convergence of such algorithms may be jeopardized in the presence of non-Gaussian noise signals, characterized by a marked impulsiveness (and infinite second-order moments), such as are frequently encountered in real-world acoustic settings. ANC methods have been recently extended to deal with such signals, modifying the weight update of the adaptive filter so that out-of-range samples are discarded or discounted. These methods require precise a priori knowledge of the impulsive characteristics of the noise and are generally not suitable for signals where such characteristics are time-varying. This work introduces an algorithm, based on an adaptive box-plot approach for outlier detection, which does not rely on any a priori information and yields uniformly high attenuation performance in all conditions tested in simulation.
选择性离群值消除脉冲噪声的主动噪声控制
传统的主动噪声控制(ANC)方法是基于自适应滤波算法,旨在使噪声方差最小化。这种算法的收敛性可能会在非高斯噪声信号的存在下受到损害,这些信号的特征是明显的冲动性(和无限的二阶矩),例如在现实世界的声学设置中经常遇到。ANC方法最近被扩展到处理这样的信号,修改自适应滤波器的权重更新,使超出范围的样本被丢弃或贴现。这些方法需要对噪声的脉冲特性有精确的先验知识,通常不适用于这些特性时变的信号。这项工作介绍了一种基于自适应箱线图方法的离群值检测算法,该算法不依赖于任何先验信息,并在模拟测试的所有条件下产生一致的高衰减性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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