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| Received:October 28, 2009Revised:August 17, 2010 |
| 基金项目:This work was partly supported by the National Natural Science Foundation of China (No. 60974017), and partly by the Specialized Research Fund for Doctoral Program of High Education, China (No. 200803370002). |
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| Exponential stability analysis for neutral BAM neural networks with time-varying delays and stochastic disturbances |
| Bo CHEN,Li YU,Wen’an ZHANG |
| (College of Information Engineering, Zhejiang University of Technology; Zhejiang Provincial United Key Laboratory of Embedded Systems) |
| Abstract: |
| This paper is concerned with the global exponential stability analysis problem for a class of neutral bidirectional 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. Furthermore, 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. |
| Key words: Neutral stochastic BAM neural networks Exponential stability Time-varying delays Linear matrix inequalities (LMIs) |
