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International Conference on Communications and Networking in China

ChinaCom 2018: Communications and Networking pp 184–193Cite as

Tracking Performance of Improved Convex Combination Adaptive Filter Based on Maximum Correntropy Criterion

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Abstract

A convex combination adaptive filter based on maximum correntropy criterion (CMCC) was widely used to solve the contradiction between the step size and the misadjustment in impulsive interference. However, one of the major drawbacks of the CMCC is its poor tracking ability. In order to solve this problem, this paper proposes an improved convex combination based on the maximum correntropy criterion (ICMCC), and investigates its estimation performance for system identification in the presence of non-Gaussian noise. The proposed ICMCC algorithm implements the combination of arbitrary number of maximum correntropy criterion (MCC) based adaptive filters with different adaption steps. Each MCC filter in the ICMCC is capable of tracking a specific change speed, such that the combined filter can track a variety of the change speed of weight vectors. In terms of normalized mean square deviation (NMSD) and tracking speed, the proposed algorithm shows good performance in the system identification for four non-Gaussian noise scenarios.

This work was supported in part by the National Natural Science Foundation of China under Grant No. 61271262, and in part by the Special Fund for Basic Scientific Research of Central Colleges, Chang’an University (310824171004).

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Authors and Affiliations

  1. School of Information Engineering, Chang’an University, Xi’an, 710064, P. R. China

    Wenjing Wu, Zhonghua Liang, Qianwen Luo & Wei Li

Authors
  1. Wenjing Wu
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  2. Zhonghua Liang
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  3. Qianwen Luo
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  4. Wei Li
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Correspondence to Zhonghua Liang .

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Editors and Affiliations

  1. School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China

    Xingang Liu

  2. University of Electronic Science and Technology of China, Chengdu, China

    Dai Cheng

  3. University of Electronic Science and Technology of China, Chengdu, China

    Lai Jinfeng

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Wu, W., Liang, Z., Luo, Q., Li, W. (2019). Tracking Performance of Improved Convex Combination Adaptive Filter Based on Maximum Correntropy Criterion. In: Liu, X., Cheng, D., Jinfeng, L. (eds) Communications and Networking. ChinaCom 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 262. Springer, Cham. https://doi.org/10.1007/978-3-030-06161-6_18

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  • DOI: https://doi.org/10.1007/978-3-030-06161-6_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-06160-9

  • Online ISBN: 978-3-030-06161-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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