ASYMPTOTIC STABILITIES OF STOCHASTIC FUNCTIONAL DIFFERENTIAL EQUATIONS

被引:0
|
作者
沈轶
江明辉
廖晓昕
机构
[1] P. R. China
[2] Department of Control Science and Engineering Huazhong University of Science and Technology
[3] Wuhan 430074
基金
中国国家自然科学基金;
关键词
stochastic functional differential equation; stochastic neural network; asymptotic stability; semi-martingale convergence theorem; Ito formula;
D O I
暂无
中图分类号
TP183 [人工神经网络与计算];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Asymptotic characteristic of solution of the stochastic functional differential equation was discussed and sufficient condition was established by multiple Lyapunov functions for locating the limit set of the solution. Moreover, from them many effective criteria on stochastic asymptotic stability, which enable us to construct the Lyapunov functions much more easily in application, were obtained. The results show that the well-known classical theorem on stochastic asymptotic stability is a special case of our more general results. In the end, application in stochastic Hopfield neural networks is given to verify our results.
引用
收藏
页码:1577 / 1584
页数:8
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