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Euclidean direction search algorithm with maximum correntropy criterion for active noise control system
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AI
DOI：10.1016/j.sigpro.2024.109759.png)
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Abstract
En 中文
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.
Keywords:
Active noise control
Euclidean direction search
Maximum correntropy criterion
Convergence behavior
Steady-state analysis
Impulsive noise
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