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A Kernel-Width Adaption Diffusion Maximum Correntropy Algorithm

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posted on 2020-02-13, 15:43 authored by Ying Guo, Bing Ma, Yingsong LiYingsong Li
In this paper, a diffusion maximum correntropy criterion (DMCC) algorithm with adaption kernel width is proposed, denoting as DMCC$_{\rm adapt}$ algorithm, to find out a solution for dynamically choosing the kernel width. The DMCC$_{\rm adapt}$ algorithm chooses small kernel width at initial stage to improve its convergence speed rate, and uses large kernel width at completion stage to reduce its steady-state error. To render the proposed DMCC$_{\rm adapt}$ algorithm suitable for sparse system identifications, the DMCC$_{\rm adapt}$ algorithm based on proportional coefficient adjustment is realized and named as diffusion proportional maximum correntropy criterion (DPMCC$_{\rm adapt}$). The theoretical analysis and simulation results are presented to show that the DPMCC$_{\rm adapt}$ and DMCC$_{\rm adapt}$ algorithms have better convergence than the traditional diffusion AF algorithms under impulse noise and sparse systems.


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Submitting Author's Institution

Harbin Engineering University

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  • China