带脉冲的随机Hopfield型神经网络的p阶矩稳定性被引量：2

The p-moment Stability for Stochastic Hopfield-type Neural Networks with Impulses

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摘要本文主要研究p阶矩意义下带脉冲的随机Hopfield型神经网络平衡点的随机指数稳定性。通过构造适当的Lyapunov泛函和利用随机分析理论,推导出平衡点稳定满足的条件。结果以不等式形式给出,使得结论更容易被验证。而且,本文给出求解算法,通过一数值算例,验证了算法的有效性。 The paper mainly concerns the stochastically exponential stability in the p-moment of the equilibrium point for a class of stochastic Hopfield-type neural networks with impulses （SHNNswI）, by constructing a Lyapunov functional and using the theory of stochastic analysis. The results is given in the form of inequalities, they can be verified much more easily. Furthermore, the algorithm is given, whose effciency is illustrated by an example.

作者卢俊香段献葆付蓉

机构地区西安工程大学理学院西安理工大学理学院

出处《工程数学学报》 CSCD 北大核心 2010年第4期741-746,共6页 Chinese Journal of Engineering Mathematics

基金 The Science Foundation for Youths of Shanxi Province(2010JQ1016) the National Natural Science Foundation of China(10926152) the Science Research Foundation of Department of Education of Shaanxi Province(9JK613)

关键词 HOPFIELD型神经网络 ITO公式 LYAPUNOV泛函随机稳定性 Hopfield-type neural networks Ito formula Lyapunov functional stochastic stability

分类号 O211.63 [理学—概率论与数理统计] O175.13 [理学—基础数学]

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