随机时滞Hopfield型神经网络的几乎指数稳定性  

Almost Surely Exponential Stability of a Hopfield Type Stochastic Neural Network with Time Delay

作　　者：王晓慧[1] 许永龙[1] 

机构地区：[1]天津师范大学管理学院,天津300384

出　　处：《天津师范大学学报（自然科学版）》2006年第2期41-44,共4页Journal of Tianjin Normal University：Natural Science Edition

基　　金：国家自然科学基金资助项目(70072039);天津社会科学基金资助项目(TJ05-GL012)

摘　　要：利用Lyapunov泛函和It^o公式,研究了具有时滞的随机Hopfield型神经网络的几乎指数稳定性,证明了一个定理和两个推论.当随机扰动为0时,得到确定性的时滞神经网络指数稳定性的结果.The almost surely exponential stability of a Hopfield type stochastic neural network was studied by using the Lyapunov function and Ito formula, and a theorem and two corollaries were proved. The results showed that when the stochastic perturbation was zero, the network became a deterministic type.

关 键 词：神经网络 随机扰动 时滞 几乎指数稳定性 

分 类 号：O211.6[理学—概率论与数理统计]