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A family of threshold based robust adaptive algorithms for active impulsive noise control

机译：主动脉冲噪声控制的基于阈值的鲁棒自适应算法

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摘要

The common active noise control (ANC) algorithm, namely the filtered-x least mean square (FxLMS) algorithm, becomes unstable for the non-Gaussian impulsive noise. This is because the typical FxLMS algorithm is based on the minimization of variance of the error signal (the second order moment in L-2 space), which does not exist for the non-Gaussian impulsive noise. In this study, a family of threshold based algorithms is proposed by minimizing several robust objective error functions as well as thresholding the reference signal to further refine the robustness of the ANC system for impulsive noise. The proposed algorithms are also expected to generalize the existing adaptive algorithms for impulsive noise control. These robust error functions are typically represented by (1) robust space vectors: L-p and Log space; and (2) re-descending M-estimators: Huber, Fair and Hampel threshold functions. The threshold parameters in the reference signal and those M-estimators can be determined by using online and/or offline statistical estimation approaches. Numerical simulations are carried out to verify the performance of proposed algorithms by using synthesized impulsive noise following symmetric alpha-stable (S alpha S) distribution. Results show the improved robustness and convergence performance of the proposed algorithms for ANC of impulsive noises as compared to the conventional algorithms. (C) 2015 Elsevier Ltd. All rights reserved.
机译：对于非高斯脉冲噪声，通用有源噪声控制（ANC）算法，即滤波X最小均方（FxLMS）算法变得不稳定。这是因为典型的FxLMS算法基于最小化误差信号（L-2空间中的二阶矩）的方差，对于非高斯脉冲噪声而言，这是不存在的。在这项研究中，通过最小化几个鲁棒的客观误差函数以及对参考信号进行阈值化以进一步完善ANC系统对脉冲噪声的鲁棒性，提出了一种基于阈值的算法。期望所提出的算法能够推广现有的用于脉冲噪声控制的自适应算法。这些鲁棒误差函数通常由（1）鲁棒空间向量表示：L-p和Log空间； （2）重新降低M估计量：Huber，Fair和Hampel阈值函数。参考信号中的阈值参数和那些M估计器可以通过使用在线和/或离线统计估计方法来确定。通过使用遵循对称α稳定（S alpha S）分布的合成脉冲噪声，进行了数值模拟，以验证所提出算法的性能。结果表明，与传统算法相比，所提出的脉冲噪声ANC算法具有更高的鲁棒性和收敛性能。 （C）2015 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Applied Acoustics》 |2015年第10期|30-36|共7页
  • 作者

    Sun Guohua; Li Mingfeng; Lim Teik C.;

  • 作者单位

    Univ Cincinnati, Coll Engn & Appl Sci, Vibroacoust & Sound Qual Res Lab, Dept Mech & Mat Engn, Cincinnati, OH 45221 USA;

    Univ Cincinnati, Coll Engn & Appl Sci, Vibroacoust & Sound Qual Res Lab, Dept Mech & Mat Engn, Cincinnati, OH 45221 USA;

    Univ Cincinnati, Coll Engn & Appl Sci, Vibroacoust & Sound Qual Res Lab, Dept Mech & Mat Engn, Cincinnati, OH 45221 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Active noise control; FxLMS algorithm; Impulsive noise; M-estimator; FxLMM algorithm;

    机译：主动噪声控制;FxLMS算法;脉冲噪声;M估计器;FxLMM算法;

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