Delay-Dependent Criterion for Exponential Stability Analysis of Neural Networks with Time-Varying Delays

被引：3
|
作者：
Farnam, Arash [1 ]
Esfanjani, Reza Mahboobi [2 ]
Ahmadi, Aghil [3 ]
机构：
[1] Univ Ghent, SYSTeMS Res Grp, B-9000 Ghent, Belgium
[2] Sahand Univ Technol, Dept Elect Engn, Tabriz, Iran
[3] Urmia Univ, Microelect Res Ctr, Orumiyeh, Iran
来源：
IFAC PAPERSONLINE | 2016年 / 49卷 / 10期
关键词：
Exponential Stability; Neural Networks; Time-Varying Delay; Linear Matrix Inequality; ASYMPTOTIC STABILITY;
D O I：
10.1016/j.ifacol.2016.07.501
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 note investigates the problem of exponential stability of neural networks with time-varying delays. To derive a less conservative stability condition, a novel augmented Lyapunov-Krasovskii functional (LKF) which includes triple and quadruple-integral terms is employed. In order to reduce the complexity of the stability test, the convex combination method is utilized to derive an improved delay dependent stability criterion in the form of linear matrix inequalities (LMIs). The superiority of the proposed approach is demonstrated by two comparative examples. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All right reserved.
引用
收藏
页码：130 / 135
页数：6
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