Theoretical convergence analysis of complex Gaussian kernel LMS algorithm

作     者：Wei Gao Jianguo Huang Jing Han Qunfei Zhang 

作者机构：School of Marine Science and TechnologyNorthwestern Polytechnical University 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2016年第27卷第1期

页      面：39-50页

核心收录：

学科分类：08[工学] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China(61001153 61271415 61401499 61531015) the Fundamental Research Funds for the Central Universities(3102014JCQ01010 3102014ZD0041) the Opening Research Foundation of State Key Laboratory of Underwater Information Processing and Control(9140C231002130C23085) 

主　　题：nonlinear adaptive filtering complex Gaussian kernel convergence analysis non circular data kernel least mean square(KLMS). 

摘      要：With the vigorous expansion of nonlinear adaptive filtering with real-valued kernel functions,its counterpart complex kernel adaptive filtering algorithms were also sequentially proposed to solve the complex-valued nonlinear problems arising in almost all real-world *** paper firstly presents two schemes of the complex Gaussian kernel-based adaptive filtering algorithms to illustrate their respective *** the theoretical convergence behavior of the complex Gaussian kernel least mean square（LMS） algorithm is studied by using the fixed dictionary *** simulation results demonstrate that the theoretical curves predicted by the derived analytical models consistently coincide with the Monte Carlo simulation results in both transient and steady-state stages for two introduced complex Gaussian kernel LMS algonthms using non-circular complex *** analytical models are able to be regard as a theoretical tool evaluating ability and allow to compare with mean square error（MSE） performance among of complex kernel LMS（KLMS） methods according to the specified kernel bandwidth and the length of dictionary.