Exponential stability analysis for neutral BAM neural networks with time-varying delays and stochastic disturbances  

作　　者：Bo CHEN Li YU Wen＇ an ZHANG 

机构地区：[1]College of Information Engineering, Zhejiang University of Technology, Hangzhou Zhejiang 310023, China [2]Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou Zhejiang 310032, China

出　　处：《控制理论与应用（英文版）》2012年第1期92-99,共8页

基　　金：partly supported by the National Natural Science Foundation of China (No. 60974017);partly by the Specialized Research Fund for Doctoral Program of High Education, China (No. 200803370002)

摘　　要：This paper is concerned with the global exponential stability analysis problem for a class of neutral bidi- rectional associative memory （BAM） neural networks with time-varying delays and stochastic disturbances. The stochastic disturbances are described by state-dependent stochastic processes. By utilizing an appropriately constructed Lyapunov- Krasovskii functional （LKF） and some stochastic analysis approaches, novel delay-dependent conditions are established in terms of linear matrix inequalities （LMIs）, which can be easily solved by existing convex optimization techniques. Further- more, the exponential convergence rate can be estimated based on the obtained results. An illustrate example is given to demonstrate the effectiveness of the proposed methods.This paper is concerned with the global exponential stability analysis problem for a class of neutral bidi- rectional associative memory （BAM） neural networks with time-varying delays and stochastic disturbances. The stochastic disturbances are described by state-dependent stochastic processes. By utilizing an appropriately constructed Lyapunov- Krasovskii functional （LKF） and some stochastic analysis approaches, novel delay-dependent conditions are established in terms of linear matrix inequalities （LMIs）, which can be easily solved by existing convex optimization techniques. Further- more, the exponential convergence rate can be estimated based on the obtained results. An illustrate example is given to demonstrate the effectiveness of the proposed methods.

关 键 词：Neutral stochastic BAM neural networks Exponential stability Time-varying delays Linear matrix inequalities （LMIs） 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP273.2[自动化与计算机技术—控制科学与工程]