New global asymptotic stability criterion for neural networks with discrete and distributed delays

被引：20

作者：

Shi, Peng

Zhang, Jinhui

Qiu, Jiqing ^{[1
]}

Xing, L'inan

机构：

[1] Hebei Univ Sci & Technol, Coll Sci, Shijiazhuang 050018, Peoples R China

[2] Univ Glamorgan, Sch Technol, Pontypridd CF37 1DL, M Glam, Wales

[3] Hebei Univ Sci & Technol, Sch Environm Sci & Engn, Shijiazhuang 050018, Peoples R China

来源：

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING | 2007年 / 221卷 / I1期

关键词：

neural networks; time-varying delay; distributed delay; global asymptotic stability; linear matrix inequalities;

D O I：

10.1243/09596518JSCE287

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 paper investigates the problem of global asymptotic stability for a class of neural networks with time-varying and distributed delays. By the Lyapunov-Krasovskii functional approach, a new delay-dependent stability criterion is derived in terms of linear matrix inequalities (LMIs). The new stability condition does not require the time delay function to be continuously differentiable and its derivative to be less than 1, and it allows the time delay to be a fast time-varying function. Simulation examples are given to demonstrate the effectiveness of the developed techniques.

引用

页码：129 / 135

页数：7

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