A new LMI condition for delay-dependent asymptotic stability of delayed Hopfield neural networks

被引：172

作者：

Xu, SY ^{[1
]}

Lam, J

Ho, DWC

机构：

[1] Nanjing Univ Sci & Technol, Dept Automat, Nanjing 210094, Peoples R China

[2] Univ Hong Kong, Dept Mech Engn, Hong Kong, Hong Kong, Peoples R China

[3] City Univ Hong Kong, Dept Math, Hong Kong, Hong Kong, Peoples R China

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS | 2006年 / 53卷 / 03期

关键词：

global asymptotic stability; Hopfield neural networks; linear matrix inequality; time delays;

D O I：

10.1109/TCSII.2005.857764

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, a new delay-dependent asymptotic stability condition for delayed Hopfield neural networks is given in terms of a linear matrix inequality, which is less conservative than existing ones in the literature. This condition guarantees the existence of a unique equilibrium point and its global asymptotic stability of a given delayed Hopfield neural network. Examples are provided to show the reduced conservatism of the proposed condition.

引用

页码：230 / 234

页数：5

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