Dissipativity analysis of stochastic neural networks with time delays
Dissipativity analysis of stochastic neural networks with time delays
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DOI：
10.1007/s11071-012-0499-7
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发表时间：
2012-06
影响因子：
5.6
通讯作者：
Zhengguang Wu;Ju H. Park;H. Su;J. Chu
中科院分区：
文献类型：
--
作者：
Zhengguang Wu;Ju H. Park;H. Su;J. Chu
本文研究具有时滞的随机神经网络的耗散性问题。首次提出了一个新的随机积分不等式。利用时滞分割技术，结合随机积分不等式，得到了系统均方指数稳定性和耗散性的充分条件。文中还考虑了一些特殊情况。文中给出的结果不仅与时延有关，还与时延划分的个数有关。最后给出了一些数值算例，说明了所提准则的有效性和改进。
This paper is concerned with the dissipativity problem of stochastic neural networks with time delay. A new stochastic integral inequality is first proposed. By utilizing the delay partitioning technique combined with the stochastic integral inequalities, some sufficient conditions ensuring mean-square exponential stability and dissipativity are derived. Some special cases are also considered. All the given results in this paper are not only dependent upon the time delay, but also upon the number of delay partitions. Finally, some numerical examples are provided to illustrate the effectiveness and improvement of the proposed criteria.