Novel robust stability criteria for interval-delayed Hopfield neural networks

Author

Liao, Xiaofeng ; Wong, Kwok-Wo ; Wu, Zhongfu ; Chen, Guanrong

Author_Institution

Dept. of Comput. Sci. & Eng., Chongqing Univ., China

Volume

48

Issue

11

fYear

2001

fDate

11/1/2001 12:00:00 AM

Firstpage

1355

Lastpage

1359

Abstract

In this paper, some novel criteria for the global robust stability of a class of interval Hopfield neural networks with constant delays are given. Based on several new Lyapunov functionals, delay-independent criteria are provided to guarantee the global robust stability of such systems. For conventional Hopfield neural networks with constant delays, some new criteria for their global asymptotic stability are also easily obtained. All the results obtained are generalizations of some recent results reported in the literature for neural networks with constant delays. Numerical examples are also given to show the correctness of the analysis

Keywords

Hopfield neural nets; Lyapunov methods; asymptotic stability; delays; stability criteria; Lyapunov functionals; constant delays; delay-independent criteria; global asymptotic stability; global robust stability; interval Hopfield neural networks; positive constant; stability bounds; Application software; Asymptotic stability; Computer science; Delay effects; Fluctuations; Hopfield neural networks; Information processing; Neural networks; Robust stability; Very large scale integration;

fLanguage

English

Journal_Title

Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on

Publisher

ieee

ISSN

1057-7122

Type

jour

DOI

10.1109/81.964428

Filename

964428