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International Conference on Communications and Networking in China

ChinaCom 2019: Communications and Networking pp 297–306Cite as

Multi-convex Combination Adaptive Filtering Algorithm Based on Maximum Versoria Criterion (Workshop)

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Abstract

Aiming at the contradiction between the convergence rate and steady state mean square error of adaptive filter based on Maximum Versoria Criterion (MVC), this paper introduces the multi-convex combination strategy into MVC algorithm, and proposes a multi-convex combination MVC (MCMVC) algorithm. Simulation results show that compared with the existing MVC algorithm, MCMVC algorithm can select the best filter more flexibly under different weight change rates, and thus it has faster convergence speed and stronger tracking ability. Moreover, compared with the existing multi-convex combination maximum correntropy criterion (MCMCC) algorithm, MCMVC algorithm not only ensures the tracking performance, but also has lower exponential computation and steady-state error.

This work was supported in part by the National Natural Science Foundation of China under Grant 61271262 and Grant 61871314, and in part by the Fundamental Research Funds for the Central Universities, CHD under Grant 300102249303 and Grant 300102249107.

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Authors and Affiliations

  1. School of Information Engineering, Chang’an University, Xi’an, 710064, People’s Republic of China

    Wenjing Wu, Zhonghua Liang, Yimeng Bai & Wei Li

Authors
  1. Wenjing Wu
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  2. Zhonghua Liang
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  3. Yimeng Bai
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  4. Wei Li
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Corresponding author

Correspondence to Zhonghua Liang .

Editor information

Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Honghao Gao

  2. School of Computer Software, Tianjin University, Tianjin, China

    Zhiyong Feng

  3. Hangzhou Dianzi University, Hangzhou, China

    Jun Yu

  4. Tongji University, Shanghai Shi, China

    Jun Wu

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Wu, W., Liang, Z., Bai, Y., Li, W. (2020). Multi-convex Combination Adaptive Filtering Algorithm Based on Maximum Versoria Criterion (Workshop). In: Gao, H., Feng, Z., Yu, J., Wu, J. (eds) Communications and Networking. ChinaCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 313. Springer, Cham. https://doi.org/10.1007/978-3-030-41117-6_24

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  • DOI: https://doi.org/10.1007/978-3-030-41117-6_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-41116-9

  • Online ISBN: 978-3-030-41117-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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