Stability Analysis of Stochastic Neural Networks with Time-Varying Delays

Author

Zhao, Zhenjiang ; Song, Qiankun

Author_Institution

Dept. of Math., Huzhou Teachers Coll., Huzhou, China

fYear

2011

fDate

28-29 May 2011

Firstpage

1

Lastpage

4

Abstract

In this paper, the global asymptotic stability is investigated for a class of stochastic neural networks with time-varying delay and generalized activation functions. By constructing appropriate Lyapunov-Krasovskii functional, and employing the free-weighting matrix method and stochastic analysis technique, a delay-dependent criterion for checking the global asymptotic stability of the addressed neural networks is established in terms of linear matrix inequalities (LMIs), which can be solved easily by using the effective LMI toolbox in MATLAB.

Keywords

Lyapunov methods; asymptotic stability; delays; linear matrix inequalities; neural nets; stochastic systems; LMI toolbox; Lyapunov-Krasovskii functional; MATLAB; delay-dependent criterion; free-weighting matrix method; generalized activation function; global asymptotic stability; linear matrix inequalities; stability analysis; stochastic analysis technique; stochastic neural network; time-varying delay; Artificial neural networks; Asymptotic stability; Biological neural networks; Delay; Stability criteria; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems and Applications (ISA), 2011 3rd International Workshop on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-9855-0

Electronic_ISBN

978-1-4244-9857-4

Type

conf

DOI

10.1109/ISA.2011.5873438

Filename

5873438