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Adaptive Filtering Under a Variable Kernel Width Maximum Correntropy Criterion | IEEE Journals & Magazine | IEEE Xplore

Adaptive Filtering Under a Variable Kernel Width Maximum Correntropy Criterion


Abstract:

The maximum correntropy criterion (MCC) algorithm with constant kernel width leads to a tradeoff problem in terms of convergence rate and steady-state misalignment. Thus,...Show More

Abstract:

The maximum correntropy criterion (MCC) algorithm with constant kernel width leads to a tradeoff problem in terms of convergence rate and steady-state misalignment. Thus, this brief proposes a variable kernel width (VKW) MCC algorithm to overcome this problem. The optimal kernel width of the proposed VKW-MCC algorithm is calculated at each iteration by maximizing exp(-ek2/2σk2) with respect to the kernel width σk, wherein the kernel width is a function of the error, to make the error with greatest attenuation along the direction of the gradient ascent. Simulations in the contexts of system identification and echo cancellation have demonstrated that the proposed VKW-MCC algorithm yields a superior performance.
Page(s): 1247 - 1251
Date of Publication: 17 February 2017

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