A New Kernel-Width Adaptation Method for Minimum Error Entropy 


Vol. 46,  No. 7, pp. 1131-1137, Jul.  2021
10.7840/kics.2021.46.7.1131


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  Abstract

Minimum error entropy (MEE) as a method of information theoretic learning has been effectively used in many applications such as channel equalization, machine learning and automatic control in Gaussian or non-Gaussian noise environments. The choice of kernel width is very sensitive and has important effects on system performance. The conventional kernel width adaptation methods based on optimization of error probability density estimation lead the kernel width to converge to the square root of 2 times of error variance (a very small value in the steady state), therefore, the error power increases in white noise situations and the width can have sudden rises in impulsive noise environments. In this paper, by applying average rate of change of error power over the small width interval to kernel width adjustment, a new kernel width adjustment method directly controlling system error is proposed. In the experiment of channel equalization, the proposed method shows the same stable learning convergences in both noise environments and yields significantly widened ranges of kernel width selection for the applications of MEE.

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  Cite this article

[IEEE Style]

N. Kim, "A New Kernel-Width Adaptation Method for Minimum Error Entropy," The Journal of Korean Institute of Communications and Information Sciences, vol. 46, no. 7, pp. 1131-1137, 2021. DOI: 10.7840/kics.2021.46.7.1131.

[ACM Style]

Namyong Kim. 2021. A New Kernel-Width Adaptation Method for Minimum Error Entropy. The Journal of Korean Institute of Communications and Information Sciences, 46, 7, (2021), 1131-1137. DOI: 10.7840/kics.2021.46.7.1131.

[KICS Style]

Namyong Kim, "A New Kernel-Width Adaptation Method for Minimum Error Entropy," The Journal of Korean Institute of Communications and Information Sciences, vol. 46, no. 7, pp. 1131-1137, 7. 2021. (https://doi.org/10.7840/kics.2021.46.7.1131)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880