Identification of linear models by fuzzy basis functions

被引：2
|
作者：
Demenkov, N. P. [1 ]
Mikrin, E. A. [1 ]
Mochalov, I. A. [1 ]
机构：
[1] Bauman Moscow State Tech Univ, Moscow, Russia
来源：
IFAC PAPERSONLINE | 2018年 / 51卷 / 32期
关键词：
hybrid data; fuzzy estimation; least squares method; fully fuzzy system of linear equations;
D O I：
10.1016/j.ifacol.2018.11.484
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This article reviews the application of the least squares method for the processing of hybrid data. We formulated and solved the problem of fuzzy estimation of the parameters of a model with fuzzy basis functions, during the solution of which fully fuzzy systems of linear equations appear. In order to illustrate the solution of the problem by the inverse matrix method, two fuzzy basis functions are reviewed: fuzzy unit and fuzzy linear dependence. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
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页码：574 / 579
页数：6
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