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Diffusion Variable Step Size Algorithm Based on Maximum Correntropy Criterion

机译:基于最大正轮堆标准的扩散可变步长算法

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摘要

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).
机译:作为一种新的方法,使用核心函数的局部相似度测量,最大的控制标准在非高斯噪声环境中具有更好的性能。为了加速算法的收敛速度,本文介绍了通过最大正轮堆标准启发的可变步长方法,提出了一种基于最大相关标准(VSS-DMCC)的可变步长分布算法。仿真结果表明,我们的算法具有比最小均方可变步长分布式分布式算法(VSS-DLMS)和最大正控性标准分布式算法(DMCC)的稳态误差较小且更快的收敛速度。

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