Blind nonlinear system identification based on LS-SVM

被引：0
|
作者：
Zhu, Yanfei [1 ]
Zhang, Yun
Tan, Hongzhou
Li, Zhonghua
机构：
[1] Guangdong Univ Tecnol, Coll Automat, Guangzhou 510006, Peoples R China
[2] Sun Yat Sen Univ, Sch Informat Sci & Technol, Guangzhou 510275, Peoples R China
来源：
DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS | 2006年 / 13卷
关键词：
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
A novel blind nonlinear system identification algorithm 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. Simulation results demonstrate the effectiveness of this approach.
引用
收藏
页码：658 / 661
页数：4
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