基于LS-SVM的非线性系统盲辨识

广东工业大学学报 ›› 2007, Vol. 24 ›› Issue (2): 76-79.

基于LS-SVM的非线性系统盲辨识

广东工业大学自动化学院；中山大学信息科学与技术学院；广东工业大学自动化学院广东广州510090；广东广州510275；广东广州510090；

出版日期:2007-07-02 发布日期:2007-07-02
基金资助:
国家自然科学基金资助项目(60575006)

Blind Nonlinear System Identification Based on LS-SVM

(1.Faculty of Automation,Guangdong University of Technology,Guangzhou 510090,China;2.School of Information Science and Technology,Sun Yat-Sen University,Guangzhou 510275,China)

Online:2007-07-02 Published:2007-07-02

摘要/Abstract

摘要： 针对现今在非线性系统盲辨识研究中遇到的困难,提出了一种基于最小二乘支持向量机(LS-SVM)的非线性系统盲辨识方法.该方法直接对非线性系统输出进行过采样,运用LS-SVM非线性建模技术,并结合输入的分布特性,从而完成非线性系统的盲辨识.介绍了盲系统辨识问题的研究内容及过采样技术原理,对LS-SVM的盲系统辨识机理和算法步骤进行了阐述.仿真结果表明了该方法在解决非线性系统盲辨识问题上的切实可行性.

关键词: 盲辨识；支持向量机；过采样；

Abstract: To solve the nonlinear problems in blind system identification,a novel blind nonlinear system identification approach based on Least-Square Support Vector Machines(LS-SVM) is investigated in this paper.By oversampling the system outputs,more information of the system characteristics can be observed to blindly identify nonlinear systems.The LS-SVM based mathematical approximation provides an adequate modeling of the unknown system given the distribution knowledge of the system inputs.The paper de...

Key words: blind identification； nonlinear system； support vector machines； oversampling；

朱燕飞；谭洪舟；章云； . 基于LS-SVM的非线性系统盲辨识[J]. 广东工业大学学报, 2007, 24(2): 76-79.

ZHU Yan-fei1,TAN Hong-zhou2,ZHANG Yun1. Blind Nonlinear System Identification Based on LS-SVM[J]. Journal of Guangdong University of Technology, 2007, 24(2): 76-79.

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