一类含分布时滞的随机Hopfield神经网络的指数稳定性  

Exponential Stability of Stochastic Hopfield Neural Networks with Distributed Delay

作　　者：张秀英[1] 李树勇[1] 赵亮[1] 杜启凤[1] 

机构地区：[1]四川师范大学数学与软件科学学院,四川成都610066

出　　处：《西华师范大学学报（自然科学版）》2015年第4期325-330,335,共7页Journal of China West Normal University(Natural Sciences)

基　　金：国家自然科学基金(11271270);四川省教育厅重点课题(10ZA125)

摘　　要：一类含分布时滞的随机Hopfield神经网络的稳定性被研究.通过构造恰当的Lyapunov泛函,利用分析技巧并借助非负半鞍收敛定理,该系统平凡解均方指数稳定和几乎必然指数稳定的充分条件被建立.通过一个例子,阐明文中结果的有效性.In this paper, stability of stochastic Hopfield neural network with distributed delay was discussed. By constructing suitable Lyapunov functional and using analysis techniques and semi-martingale convergence theorem, a new sufficient condition to guarantee the mean square exponential stability and almost sure exponential stability for the system was presented. One example was given to show the applicability of the proposed approach.

关 键 词：随机Hopfiled神经网络 分布时滞 LYAPUNOV泛函 非负半鞍收敛定理 几乎必然指数稳定 均方指数稳定 

分 类 号：O175.21[理学—数学] TN911.23[理学—基础数学]