采用最大熵准则的欧氏方向搜索算法用于主动噪声控制系统

IF 3.4 2区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Signal Processing Pub Date : 2024-11-17 DOI:10.1016/j.sigpro.2024.109759

Jie Wang , Lu Lu , Zongsheng Zheng , Kai-Li Yin , Yi Yu , Long Shi

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引用次数: 0

摘要

基于叠加原理，主动噪声控制（ANC）技术可以实现令人满意的降噪效果。滤波-x 最小均方（FxLMS）算法已在 ANC 问题中得到广泛应用，但它在脉冲噪声情况下很容易陷入不稳定。为了改善这一缺点，利用欧氏方向搜索算法（EDS）的计算量减少和最大熵准则（MCC）的鲁棒性，提出了一种新的过滤-x EDS-MCC 算法（FxEDS-MCC）来削弱脉冲干扰。FxEDS-MCC 算法的理论分析基于旋转方法和泰勒级数展开近似。仿真验证了理论性能的准确性，并验证了与现有算法相比，FxEDS-MCC 算法的性能有所提高。

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Euclidean direction search algorithm with maximum correntropy criterion for active noise control system

Based on the principle of superposition, the active noise control (ANC) technique can achieve satisfactory noise reduction. The filtered-x least mean square (FxLMS) algorithm has been extensively implemented in the ANC problem but it is easily plunged into instability in impulsive noise scenarios. To ameliorate this disadvantage, benefiting from the reduced computational load of the Euclidean direction search (EDS) algorithm and robustness of the maximum correntropy criterion (MCC), a novel filtered-x EDS-MCC (FxEDS-MCC) algorithm is proposed to attenuate the impulsive interference. The theoretical analysis of the FxEDS-MCC algorithm is based on the rotated method and the Taylor series expansion approximation. Simulations validate the accuracy of the theoretical performance and verify the improved performance of the FxEDS-MCC algorithm in comparison with the existing algorithms.

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来源期刊

Signal Processing 工程技术-工程：电子与电气

CiteScore

9.20

自引率

9.10%

发文量

309

审稿时长

41 days

期刊介绍： Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.