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Enhanced filtered-x least mean M-estimate algorithm for active impulsive noise control

APPLIED ACOUSTICS 2015年第Apr.期90卷 31-41页

作者： Sun, Guohua Li, Mingfeng Lim, Teik C. Univ Cincinnati Coll Engn & Appl Sci Dept Mech & Mat Engn Vibro Acoust & Sound Qual Res Lab Cincinnati OH 45221 USA

Applying the typical active noise control (ANC) algorithm, namely the filtered-x least mean square (FxLMS) algorithm, to the non-Gaussian impulsive noise will experience difficulty. This is because the FxLMS algorithm is based upon the minimization of variance of the error signal, which is normally with the assumption of Gaussian distribution. To deal with this issue, the filtered-x least mean M-estimate (fxlmm) algorithm has been Opposed based on the robust statistics theory to minimize the objective M-estimator error function. The Hampel's three-part M-estimator has been applied to provide thresholds for detecting and rejecting the outliers/impulses in the error signal. To further enhance the robustness of the conventional fxlmm algorithm, in this study a modified fxlmm (Mfxlmm) algorithm is proposed, where the reference signal is fed through another Hampel's three-part M-estimator by setting thresholds for the impulsive samples. Numerous computer simulations are performed to validate the performance of the proposed algorithm. The generic impulsive noise is synthesized by using the contaminated Gaussian (CG) noise model, where certain number of impulses with different amplitudes and widths can be added in the background white Gaussian noise to represent different impulsive characteristics. In addition, extensive laboratory tests are carried out to further demonstrate the enhanced efficacy of the algorithm in a real-time environment. Results indicate that the proposed Mfxlmm algorithm with online-threshold estimation is a very promising alternative for ANC of impulsive noise, and it shows similar convergence performance as the prevalent FxLMS algorithm for noise not corrupted by impulses. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Active noise control Impulsive noise M-estimator fxlmm algorithm

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

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APPLIED ACOUSTICS 2015年第Oct.期97卷 30-36页

作者： Sun, Guohua Li, Mingfeng Lim, Teik C. Univ Cincinnati Coll Engn & Appl Sci Vibroacoust & Sound Qual Res Lab Dept Mech & Mat Engn Cincinnati OH 45221 USA

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.

关键词： Active noise control FxLMS algorithm Impulsive noise M-estimator fxlmm algorithm

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