Stochastic Exponential Stability for Markovian Jumping BAM Neural Networks With Time-Varying Delays

Author

Lou, Xuyang ; Cui, Baotong

Author_Institution

Res. Center of Control Sci. & Eng., Southern Yangtze Univ., Wuxi

Volume

37

Issue

3

fYear

2007

fDate

6/1/2007 12:00:00 AM

Firstpage

713

Lastpage

719

Abstract

This correspondence provides stochastic exponential stability for Markovian jumping bidirectional associative memory neural networks with time-varying delays. An approach combining the Lyapunov functional with linear matrix inequality is taken to study the problems. Some criteria for the stochastic exponential stability are derived. The results obtained in this correspondence are less conservative, less restrictive, and more computationally efficient than the ones reported so far in the literature

Keywords

Lyapunov methods; Markov processes; asymptotic stability; content-addressable storage; delays; linear matrix inequalities; neural nets; Lyapunov function; Markovian jumping bidirectional associative memory neural networks; linear matrix inequality; stochastic exponential stability; time-varying delays; Associative memory; Delay; Differential equations; Linear matrix inequalities; Magnesium compounds; Neural networks; Pattern recognition; Stability criteria; Stochastic processes; Symmetric matrices; Bidirectional associative memory (BAM); Markovian jumping parameters; linear matrix inequality (LMI); stochastic exponential stability; time-varying delays; Algorithms; Computer Simulation; Markov Chains; Models, Statistical; Neural Networks (Computer); Nonlinear Dynamics; Pattern Recognition, Automated; Stochastic Processes;

fLanguage

English

Journal_Title

Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on

Publisher

ieee

ISSN

1083-4419

Type

jour

DOI

10.1109/TSMCB.2006.887426

Filename

4200807