Robust stability of Markovian jumping stochastic neural networks with interval time-varying delay

Author

Fu, Jie ; Feng, Jian ; Zhang, Huaguang

Author_Institution

Sch. of Inf. Sci. & Eng., Northeastern Univ. Shenyang, Shenyang

fYear

2008

fDate

12-15 Oct. 2008

Firstpage

3630

Lastpage

3635

Abstract

This paper studies the robust stability problem for a class of Markovian jumping stochastic neural networks (MJSNNs) with interval time-varying delay. Based on Lyapunov-Krasovskii functional and stochastic analysis approach, a new delay-dependent sufficient condition is obtained in the linear matrix inequalities (LMIs) format such that for all admissible uncertainties delayed MJSNNs is globally asymptotically stable in the mean-square sense. The effectiveness of the proposed method is demonstrated by a numerical example.

Keywords

Lyapunov methods; delays; linear matrix inequalities; neural nets; stability; stochastic processes; time-varying systems; Lyapunov-Krasovskii functional; Markovian jumping stochastic neural networks; interval time-varying delay; linear matrix inequalities; robust stability; stochastic analysis; Delay effects; Filtration; Linear matrix inequalities; Neural networks; Neurons; Robust stability; Stability criteria; Stochastic processes; Switches; Uncertain systems; Interval time-varying delay; Linear matrix inequality; Markovian jumping stochastic neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics, 2008. SMC 2008. IEEE International Conference on

Conference_Location

Singapore

ISSN

1062-922X

Print_ISBN

978-1-4244-2383-5

Electronic_ISBN

1062-922X

Type

conf

DOI

10.1109/ICSMC.2008.4811862

Filename

4811862