Random sampling fuzzy c-means clustering and recursive least square based fuzzy identification

被引：0
|
作者：
Lu, Pingli [1 ]
Yang, Ying [1 ]
Ma, Wenbo [2 ]
机构：
[1] Peking Univ, Ctr Syst & Control, Dept Engn Sci & Mech, Beijing 100871, Peoples R China
[2] Beijing Inst Technol, Sch Informat Sci & Technol, Beijing 100081, Peoples R China
来源：
2006 AMERICAN CONTROL CONFERENCE, VOLS 1-12 | 2006年 / 1-12卷
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a new method of fuzzy identification based on fuzzy clustering and recursive least square is proposed. The membership degree of each given pattern is calculated by using fast fuzzy clustering algorithm and the consequent parameters are identified by recursive least square. It is shown that the computer CPU time has been greatly saved compared with fuzzy c-means clustering method. A numerical example is given at the end of the paper to demonstrate the applicability and validity of the proposed method.
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收藏
页码：5049 / +
页数：2
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