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Performance Analysis of Robust Subband Hammerstein Spline Adaptive Filter

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Abstract

This article develops a subband Hammerstein spline adaptive filtering (SHSAF) algorithm with the exponential hyperbolic cosine (EHC) cost to acquire robustness against non-Gaussian noises, which is called the SHSAF-EHC algorithm. The delayless multiband-structured subband strategy is employed to enhance the convergence property in the Hammerstein-type nonlinear filtering structure. In addition, the statistical performance analysis of SHSAF-EHC is rigorously derived in the mean and mean-square senses. Numerical experiments under non-Gaussian noise scenarios corroborate the accuracy of theoretical findings and validate the superiority of the proposed algorithm.

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Data Availability

The datasets generated or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This work was supported in part by the Natural Science Foundation of China under Grants 62201480 and 61901400, and in part by the Natural Science Foundation of Sichuan, China, under Grants 2022NSFSC0896 and 2022NSFSC0542.

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Authors and Affiliations

  1. School of Electrical Engineering and Information, Southwest Petroleum University, Chendu, 610500, China

    Tao Yu, Shijie Tan & Wenqi Li

  2. School of Automation Engineering, University of Electronic Science and Technology of China, Chendu, 611731, China

    Tianpeng Huang

  3. School of Information Engineering, Robot Technology Used for Special Environment Key Laboratory of Sichuan Province, Southwest University of Science and Technology, Mianyang, 621010, China

    Yi Yu

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  1. Tao Yu
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Correspondence to Tao Yu.

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Yu, T., Tan, S., Li, W. et al. Performance Analysis of Robust Subband Hammerstein Spline Adaptive Filter. Circuits Syst Signal Process 43, 368–387 (2024). https://doi.org/10.1007/s00034-023-02476-2

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  • DOI: https://doi.org/10.1007/s00034-023-02476-2

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