Robust active noise control: An information theoretic learning approach

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• 作者：Nikhil Cherian Kurian ; Kashyap Patel ; Nithin V. George ; ^{nithin@iitgn.ac.in}
• 关键词：Active noise control ; Adaptive filter ; Information theory ; Correntropy ; Robust algorithm
• 刊名：Applied Acoustics
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：117
• 期：part_PA
• 页码：180-184
• 全文大小：5484 K
• 卷排序：117

文摘

Nonlinear active noise control (ANC) systems, which employ a nonlinear filter as the adaptive controller is not robust when the primary noise to be mitigated has a non-Gaussian distribution. The algorithm which updates the weights of the controller may even diverge for some higher magnitude primary noise signals. With an objective to improve the robustness of nonlinear ANC systems, a correntropy based nonlinear ANC system is developed in this paper. The proposed ANC scheme uses an information theoretic learning approach and has been shown to provide robust noise mitigation even for non-Gaussian primary noise signals.