Exponential stability of static neural networks with time delay and impulses

Author

Wu, San Lein ; Li, K.-L. ; Huang, T.Z.

Author_Institution

Sch. of Math. Sci., Univ. of Electron. Sci. & Technol. of China, Chengdu, China

Volume

5

Issue

8

fYear

2011

fDate

5/1/2011 12:00:00 AM

Firstpage

943

Lastpage

951

Abstract

In this study, the authors investigate the problem of global exponential stability of static neural networks with time delay and impulses. Three types of impulses are studied: the impulses are input disturbances; the impulses are `neutral` type, that is, they are neither helpful for stability of neural networks nor destabilising; and the impulses are stabilising. For each type of impulses, by using Lyapunov function and Razumikhin-type techniques, sufficient conditions for global exponential stability are established in terms of linear matrix inequalities with respect to suitable classes of impulse time sequences. The new sufficient conditions can explicitly reveal the effects of time delay, impulses etc., on the stability. Numerical results are given to show the less conservatism of the obtained criteria compared with the existing ones.

Keywords

Lyapunov methods; asymptotic stability; delays; linear matrix inequalities; neural nets; Lyapunov function; Razumikhin-type technique; global exponential stability; linear matrix inequalities; neural network impulse; neural network time delay; static neural networks;

fLanguage

English

Journal_Title

Control Theory & Applications, IET

Publisher

iet

ISSN

1751-8644

Type

jour

DOI

10.1049/iet-cta.2010.0329

Filename

5954974