A Novel Criterion for Robust Stability of Stochastic Bidirectional Associative Memory Neural Networks with Time Delays

Author

Kan, Xiu ; Lv, Zengwei ; Shu, Huisheng

Author_Institution

Coll. of Appl. Math., Donghua Univ., Shanghai, China

Volume

2

fYear

2009

fDate

7-8 Nov. 2009

Firstpage

467

Lastpage

471

Abstract

Based on the Lyapunov-Krasovskii functionals combined with linear matrix inequality approach, a novel stability criterion is proposed for asymptotic stability of uncertain stochastic bidirectional associative memory neural networks with time delays. A novel delay-dependent stability criterion is given in terms of linear matrix inequalities.

Keywords

asymptotic stability; delays; linear matrix inequalities; neural nets; Lyapunov-Krasovskii functionals; linear matrix inequality; robust stability; stochastic bidirectional associative memory neural networks; time delays; Associative memory; Biological neural networks; Delay effects; Linear matrix inequalities; Magnesium compounds; Neural networks; Robust stability; Stability criteria; Stochastic processes; Symmetric matrices; Global robust stability; Linear matrix inequality; Lyapunov-Krasovskii functionals; Stochastic bidirectional associative memory neural networks; Stochastic systems; Time delays; Uncertain systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-3835-8

Electronic_ISBN

978-0-7695-3816-7

Type

conf

DOI

10.1109/AICI.2009.300

Filename

5375865