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Spline Adaptive Filtering Algorithm-based Generalized Maximum Correntropy and its Application to Nonlinear Active Noise Control

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Abstract

This study proposes a spline filtering algorithm-based generalized maximum correntropy criterion (GMCC), named the spline adaptive filter (SAF-)-GMCC algorithm. Compared with traditional spline algorithms, the SAF-GMCC can cope with impulsive interference effectively, because the GMCC has a low sensitivity to mutation signals. The GMCC-based variable step-size spline filtering algorithm (SAF-GMCC) is proposed to solve the limitation of the fixed step-size on the SAF-GMCC algorithm’s performance and to improve the convergence rate and steady-state error performance. Combining these algorithms with the active noise control (ANC) model, this study proposes the filtered-c generalized maximum correntropy criterion (FcGMCC) and variable step-size filtered-c generalized maximum correntropy criterion (FcVGMCC) algorithms. Finally, the nonlinear system identification model simulates an experimental environment with impulsive interference. The SAF-GMCC and SAF-VGMCC algorithms offer better robustness than the existing algorithms. And the alpha-stable noise environment simulation with different impact strengths, in the ANC model verifies the FcGMCC and FcVGMCC algorithms’ robustness in nonlinear and non-Gaussian noise environments.

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Data Availability

The data that support the findings of this study are available from the corresponding author on request.

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Acknowledgements

This work was partially supported by National Natural Science Foundation of China (Grant Nos: 62171388, 61871461, 61571374) and Fundamental Research Funds for the Central Universities (Grant No: 2682021ZTPY091).

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Authors and Affiliations

  1. Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle, Ministry of Education; School of Electrical Engineering, Southwest Jiaotong University, Chengdu, 610031, China

    Yuan Gao, Haiquan Zhao, Yingying Zhu & Jingwei Lou

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  1. Yuan Gao
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Correspondence to Haiquan Zhao.

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Gao, Y., Zhao, H., Zhu, Y. et al. Spline Adaptive Filtering Algorithm-based Generalized Maximum Correntropy and its Application to Nonlinear Active Noise Control. Circuits Syst Signal Process 42, 6636–6659 (2023). https://doi.org/10.1007/s00034-023-02411-5

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