Global exponential stability results for neutral-type impulsive neural networks

被引：99

作者：

Rakkiyappan, R. ^{[2
]}

Balasubramaniam, P. ^{[2
]}

Cao, Jinde ^{[1
]}

机构：

[1] Southeast Univ, Dept Math, Nanjing 210096, Peoples R China

[2] Gandhigram Rural Univ, Dept Math, Gandhigram 624302, Tamil Nadu, India

来源：

NONLINEAR ANALYSIS-REAL WORLD APPLICATIONS | 2010年 / 11卷 / 01期

关键词：

Lyapunov-Krasovskii functional; Linear matrix inequality; Global exponential stability; Impulsive neural networks; Neutral-type; Generalized eigenvalue problem (GEVP); DIFFERENTIAL-EQUATIONS; OPTIMIZATION; CONVERGENCE; BOUNDEDNESS; SYSTEMS;

D O I：

10.1016/j.nonrwa.2008.10.050

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, by utilizing the Lyapunov-Krasovkii functional and combining with the linear matrix inequality (LMI) approach, we analyze the global exponential stability of neutral-type impulsive neural networks. In addition, an example is provided to illustrate the applicability of the result using LMI control toolbox in MATLAB. (C) 2008 Elsevier Ltd. All rights reserved.

引用

页码：122 / 130

页数：9

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