期刊
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
卷 14, 期 4, 页码 1582-1589出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.cnsns.2008.04.009
关键词
Stochastic system; Delay-dependent; Neural networks; Mean square exponential stability
类别
资金
- Natural Science Foundation of China [60404006, 60574006]
- Natural Science Foundation of the Jiangsu Higher Education Institutions of China [07KJB510125]
In this paper, the mean square exponential stability problem is deal with for a class of uncertain stochastic neural networks with time-varying delays. By introducing a new Lyapunov-Krasovskii function, improved delay-dependent stability criteria are established in term of linear matrix inequalities (LMIs). Finally, two numerical examples are given to show that our results are less conservative and more efficiency than the existing stability criteria. (c) 2008 Elsevier B.V. All rights reserved.
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