Generalized Complex Correntropy: Application to Adaptive Filtering of Complex Data

被引:36
作者
Qian, Guobing [1 ]
Wang, Shiyuan
机构
[1] Southwest Univ, Coll Elect & Informat Engn, Chongqing 400715, Peoples R China
来源
IEEE ACCESS | 2018年 / 6卷
基金
中国国家自然科学基金;
关键词
Complex correntropy; generalized Gaussian function; robustness; zero POD; LMS;
D O I
10.1109/ACCESS.2018.2821141
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Adaptive filtering for complex data has received more attentions recently. As a similarity measure for the complex random variables, complex correntropy has been shown robustness in the design of adaptive filter. However, existing works using complex correntropy are limited to a Gaussian kernel function, which is not always the optimal choice. In this paper, we propose a class of new adaptive filtering algorithm for complex data using complex correntropy, which employs the complex generalized Gaussian density function as kernel function. Stability analysis provides the bound for learning rate and the steady-state excess mean square error is derived for theoretical analysis. Simulation results show that the proposed algorithm has zero probability of divergence and verify its superiority.
引用
收藏
页码:19113 / 19120
页数:8
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