Dynamics of fuzzy impulsive bidirectional associative memory neural networks with time-varying delays

被引：0

作者：

Rakkiyappan, R. ^{[1
]}

Li, Xiaodi ^{[2
]}

O'Regan, Donal ^{[3
]}

机构：

[1] Bharathiar Univ, Dept Math, Coimbatore 641046, Tamil Nadu, India

[2] Shandong Normal Univ, Sch Math Sci, Jinan 250014, Peoples R China

[3] Natl Univ Ireland, Dept Math, Galway, Ireland

来源：

JOURNAL OF APPLIED MATHEMATICS AND COMPUTING | 2012年 / 40卷 / 1-2期

关键词：

Exponential stability; Fuzzy impulsive BAM neural networks; Generalized eigenvalue problem (GEVP); Linear matrix inequality; Lyapunov-Krasovskii functional; Time-varying delays;

D O I：

10.1007/s12190-012-0554-z

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Complex nonlinear systems can be represented to a set of linear sub-models by using fuzzy sets and fuzzy reasoning via ordinary Takagi-Sugeno (TS) fuzzy models. In this paper, the exponential stability of TS fuzzy bidirectional associative memory (BAM) neural networks with impulsive effect and time-varying delays is investigated. The model of fuzzy impulsive BAM neural networks with time-varying delays established as a modified TS fuzzy model is new in which the consequent parts are composed of a set of impulsive BAM neural networks with time-varying delays. Further the exponential stability for fuzzy impulsive BAM neural networks is presented by utilizing the Lyapunov-Krasovskii functional and the linear matrix inequality (LMI) technique without tuning any parameters. In addition, an example is provided to illustrate the applicability of the result using LMI control toolbox in MATLAB.

引用

页码：289 / 317

页数：29

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