Acta mathematica scientia,Series A

• Articles • Previous Articles     Next Articles

Exponential Stability in Mean Square for Stochastic Hopfield Delay Neural Networks: an LMI Approach

Chen Wuhua; Lu Xiaomei; Li Qunhong; Guan Zhihong   

  1. College of Mathematics and Information Science, Guangxi University, Nanning 530004
  • Received:2004-12-14 Revised:2006-01-04 Online:2007-02-25 Published:2007-02-25
  • Contact: Chen Wuhua

Abstract: By using a technique of model transformation of the system, a new type of Lyapunov functional is introduced. By applying this new Lyapunov functional, a novel delay-dependent sufficient condition of exponential stability in mean square for stochastic Hopfield delay neural networks is derived in terms of
linear matrix inequalities (LMIs). A delay-independent sufficient condition is also presented. Numerical examples show that the proposed method is less conservative than the previous ones.

Key words: Stochastic Hopfield neural networks, Time-delay, Exponential stability in mean square, Linear matrix inequality (LMI)

CLC Number: 

  • 93D
Trendmd