An analysis of global asymptotic stability of delayed Cohen-Grossberg neural networks via. nonsmooth analysis

被引：94

作者：

Yuan, K ^{[1
]}

Cao, JD ^{[1
]}

机构：

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

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS | 2005年 / 52卷 / 09期

基金：

中国国家自然科学基金;

关键词：

Cohen-Grossberg neural networks; generalized Jacobian; global asymptotic stability; homeomorphism; Lyapunov functional; nonsmooth analysis; spectral radius;

D O I：

10.1109/TCSI.2005.852210

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, using a method based on nonsmooth analysis and the Lyapunov method, several new sufficient conditions are derived to ensure existence and global asymptotic stability of the equilibrium point for delayed Cohen-Grossberg neural networks. The obtained criteria can be checked easily in practice and have a distinguished feature from previous studies, and our results do not need the smoothness of the behaved function, boundedness of the activation function and the symmetry of the connection matrices. Moreover, two examples are exploited to illustrate the effectiveness of the proposed criteria in comparison with some existing results.

引用

页码：1854 / 1861

页数：8

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