东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2007, Vol. 28 ›› Issue (1): 6-9.DOI: -

• 论著 • 上一篇    下一篇

具有混合时滞的随机Cohen-Grossberg神经网络的稳定性分析

汪刚;张化光;付冬;   

  1. 东北大学信息科学与工程学院;东北大学信息科学与工程学院;辽宁经济职业技术学院 辽宁沈阳110004;辽宁沈阳110004;辽宁沈阳110122
  • 收稿日期:2013-06-27 修回日期:2013-06-27 出版日期:2007-01-15 发布日期:2013-06-24
  • 通讯作者: Wang, G.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(60325311,60534010,60572070)

Stability analysis of stochastic Cohen-Grossberg neural networks with mixed time delays

Wang, Gang (1); Zhang, Hua-Guang (1); Fu, Dong (2)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China; (2) Liaoning Economic Occupational Technology College, Shenyang 110122, China
  • Received:2013-06-27 Revised:2013-06-27 Online:2007-01-15 Published:2013-06-24
  • Contact: Wang, G.
  • About author:-
  • Supported by:
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摘要： 研究了均方意义下的具有时变时滞与分布时滞的随机Cohen-Grossberg神经网络的指数稳定性,利用It微分公式和Lyapunov泛函,得到了一个关于其指数稳定时滞无关的充分条件.具体实施方法是运用It微分公式沿所考虑的神经网络对构造的Lyapunov泛函进行微分,得到了系统稳定的代数判据.最后,通过一个数学样例说明了所得结论的有效性.目前文献尚未见同时具有时变时滞与分布时滞的随机Cohen-Grossberg神经网络的指数稳定性的相应结果,由于Cohen-Grossberg神经网络更具有代表性,其研究意义与应用前景不言而喻.

关键词: 随机Cohen-Grossberg神经网络, Lyapunov泛函, 均方指数稳定, 时变时滞, 分布时滞

Abstract: Mean square exponential stability of Cohen-Grossberg neural networks with time-varying delays and distributed time delays is analyzed. By using differential formula and Lyapunov functional, a new delay-independent sufficient condition for exponential stability is derived. By Itoˆ differential formula, the stochastic derivative of Lyapunov functional along the considered neural network is obtained. Finally, a numerical example is given to demonstrate the usefulness of the proposed stability criteria. To the best of our knowledge, there are few results about the mean square exponential stability analysis of Cohen-Grossberg neural networks with time-varying delays and distributed time delays. Due to the representation of Cohen-Grossberg neural networks, it is significant to study its exponential stability.

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