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

  • Wenjing Wu
  • Zhonghua LiangEmail author
  • Qianwen Luo
  • Wei Li
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 262)

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.

Keywords

Convex combination Maximum correntropy criterion (MCC); Non-Gaussian noise; Normalized mean square deviation (NMSD); System identification 

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Copyright information

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

Authors and Affiliations

  • Wenjing Wu
    • 1
  • Zhonghua Liang
    • 1
    Email author
  • Qianwen Luo
    • 1
  • Wei Li
    • 1
  1. 1.School of Information EngineeringChang’an UniversityXi’anP. R. China

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