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Robust adaptive filtering algorithm based on maximum correntropy criteria for censored regression

机译:基于最大熵准则的鲁棒自适应滤波算法

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摘要

Censored observations and impulsive measurement noise are encountered in many practical applications of adaptive signal processing. Traditional adaptive filtering algorithms may fail to work in such cases. This paper proposes a robust adaptive filter algorithm predicated on maximum correntropy criteria (MCC) for censored regression. A detailed performance analysis in terms of mean and mean-square behaviour is provided. Simulations with Gaussian and non-Gaussian noise are presented to verify the theoretical results, and to demonstrate the superior performance of the proposed algorithm over existing algorithms. (C) 2019 Elsevier B.V. All rights reserved.
机译:在自适应信号处理的许多实际应用中会遇到删失的观测结果和脉冲测量噪声。在这种情况下,传统的自适应过滤算法可能无法正常工作。本文提出了一种鲁棒的自适应滤波器算法,该算法基于最大熵准则(MCC)进行删失回归。提供了有关均值和均方行为的详细性能分析。提出了使用高斯和非高斯噪声的仿真,以验证理论结果,并证明所提出的算法优于现有算法。 (C)2019 Elsevier B.V.保留所有权利。

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