Convergence performance analysis of an adaptive kernel width MCC algorithm

A fixed kernel width in MCC algorithm imposes a trade-off among robustness, convergence rate and steady-state accuracy. With a variable kernel width, the adaptive kernel width MCC (AMCC) algorithm can improve the learning speed of the MCC algorithm especially when the initial weight vector is far aw...

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Bibliographic Details
Published in:	International journal of electronics and communications Vol. 76; pp. 71 - 76
Main Authors:	Wang, Weihua, Zhao, Jihong, Qu, Hua, Chen, Badong, Principe, Jose C.
Format:	Journal Article
Language:	English
Published:	Elsevier GmbH 01.06.2017
Subjects:	Adaptive kernel width Convergence performance analysis Maximum correntropy criterion Maximum correntropy criterion Adaptive kernel width Convergence performance analysis
ISSN:	1434-8411, 1618-0399
Online Access:	Get full text
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Summary:	A fixed kernel width in MCC algorithm imposes a trade-off among robustness, convergence rate and steady-state accuracy. With a variable kernel width, the adaptive kernel width MCC (AMCC) algorithm can improve the learning speed of the MCC algorithm especially when the initial weight vector is far away from the optimal weight vector. In this paper, the steady-state excess mean square error (EMSE) of the AMCC algorithm is studied based on energy conservation relation. In addition, a novel convergence measure called initial convergence rate is introduced to evaluate the convergence speed at the beginning of the learning. Simulation experiments are carried out to verify the theoretical analysis and confirm the desirable performance of the AMCC algorithm in several different non-Gaussian noise environments.
ISSN:	1434-8411 1618-0399
DOI:	10.1016/j.aeue.2017.03.028