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Robust gain-combined proportionate normalized subband adaptive filter algorithm with a variable control parameter step-size scaler

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Abstract

IN order to improve performance of the original normalized subband adaptive filter algorithm with the step-size scaler (SSS-NSAF) when identifying sparse impulsive response, the proportionate SSS-NSAF (SSS-PNSAF) algorithm and improved proportionate SSS-NSAF (SSS-IPNSAF) algorithms are given by utilizing common proportionate strategy. Even though the performance of the SSS-PNSAF algorithm is improved in sparse system, its convergence rate even slower than the original SSS-NSAF algorithm when the impulse response is disperse. For possessing great performance of the SSS-PNSAF algorithm in sparse impulse response and retaining merit of the SSS-NSAF algorithm in dispersive impulse response, the gain-combined proportionate SSS-NSAF (GC-SSS-PNSAF) algorithm is proposed by combining weight coefficient vectors of these two algorithms with a variable mixing parameter. The mixing parameter is indirectly updated through a modified sigmoidal activation function by using stochastic gradient method which minimizes the power of the system output errors. Furthermore, variable control parameter (VCP) mechanism is introduced to the GC-SSS-PNSAF algorithm to overcome the trade-off issue between fast convergence rate and low steady-state error. Numerous simulation experiments confirm the superiority of these proposed algorithms.

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The data used to support the findings of this study are available from the corresponding author upon request.

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Acknowledgments

This work was supported by the Open Research Fund of National Engineering Research Center for Agri-Ecological Big Data Analysis & Application, Anhui University (No. AE202209).

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Authors and Affiliations

  1. School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, China

    Zijie Shen & Lin Tang

  2. Research Center of Technological Innovation, Tsinghua University, Beijing, China

    Linna Shi

  3. Sichuan Academy of Science and Technology for Development, Chengdu, China

    Linna Shi

  4. National Engineering Research Center for Agri-Ecological Big Data Analysis & Application, Anhui University, Hefei, 230039, Anhui, China

    Lin Tang

Authors
  1. Zijie Shen
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  2. Linna Shi
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  3. Lin Tang
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Contributions

Zijie Shen wrote and revised the main manuscript text, Linna Shi prepared figures and Lin Tang calculated computaional complexity and prepared table. Then All authors reviewed the manuscript.

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Correspondence to Linna Shi.

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Shen, Z., Shi, L. & Tang, L. Robust gain-combined proportionate normalized subband adaptive filter algorithm with a variable control parameter step-size scaler. SIViP 17, 2193–2200 (2023). https://doi.org/10.1007/s11760-022-02434-6

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  • DOI: https://doi.org/10.1007/s11760-022-02434-6

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