Exponential stability of T-S fuzzy stochastic discrete-time BAM networks with delays

Author

Xing, Jun ; He, Xiqin ; Zhang, Daqing

Author_Institution

Sch. of Sci., Univ. of Sci. & Technol. Liaoning, Anshan, China

fYear

2012

fDate

June 30 2012-July 2 2012

Firstpage

276

Lastpage

281

Abstract

The problem of global robust exponential stability is investigated for Fuzzy stochastic uncertain discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays which are represented by the Takagi-Sugeno (T-S) fuzzy models. The uncertainties are assumed to be the linear fractional form. Based on Lyapunov-Krasovskii functional (LKF) method in combination with a finite sum inequality, a delay-dependent exponential stability criterion is established in terms of linear matrix inequalities (LMIs). A numerical example is provided to show the effectiveness of the proposed method.

Keywords

Lyapunov methods; asymptotic stability; content-addressable storage; delay systems; discrete time systems; fuzzy set theory; linear matrix inequalities; neural nets; stochastic processes; uncertain systems; BAM neural network; LKF method; LMI; Lyapunov-Krasovskii functional method; T-S fuzzy model; T-S fuzzy stochastic network; Takagi-Sugeno fuzzy model; bidirectional associative memory; delay-dependent exponential stability; discrete-time BAM network; finite sum inequality; fuzzy stochastic uncertain system; global robust exponential stability; linear fractional form; linear matrix inequalities; time-varying delay; Biological neural networks; Delay; Numerical stability; Stability criteria; Stochastic processes; BAM neural network; Discrete-time; Exponential stability; Lyapunov-Krasovskii functional;

fLanguage

English

Publisher

ieee

Conference_Titel

System Science and Engineering (ICSSE), 2012 International Conference on

Conference_Location

Dalian, Liaoning

Print_ISBN

978-1-4673-0944-8

Electronic_ISBN

978-1-4673-0943-1

Type

conf

DOI

10.1109/ICSSE.2012.6257190

Filename

6257190