基于最大相关熵准则的扩散变步长算法

Lin Yun, H. Xiaobin, Gao Qianqian
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引用次数: 2

摘要

最大熵准则作为一种利用核函数进行局部相似度量的新方法,在非高斯噪声环境下具有较好的性能。为了加快算法的收敛速度,引入了一种受最大相关准则启发的变步长方法,提出了一种基于最大相关准则的变步长分布式算法(VSS-DMCC)。仿真结果表明,该算法比最小均方变步长分布算法(VSS-DLMS)和最大熵准则分布算法(DMCC)具有更小的稳态误差和更快的收敛速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diffusion Variable Step Size Algorithm Based on Maximum Correntropy Criterion
As a new kind of method using localized similarity measure by kernel function, maximum correntropy criterion has the better performance in the environment of non-Gaussian noise. And in order to accelerate the convergence speed of the algorithm, this paper introduces a variable step size method inspired by maximum correntropy criterion, proposes a variable step size distributed algorithm based on maximum correlation criterion (VSS-DMCC). Simulation results show that our algorithm has smaller steady-state error and faster convergence speed than the minimum mean square variable step size distributed algorithm (VSS-DLMS) and maximum correntropy criterion distributed algorithm (DMCC).
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