一类脉冲时滞神经网络模型的周期性分析  

Periodicity Analysis for a Class of Impulsive Delayed Neural Networks

作　　者：张为元[1] 王振华 张磊磊 ZHANG Weiyuan;WANG Zhenhua;ZHANG Leilei(Institute of Nonlinear Science,Xianyang Normal University,Xianyang 712000,Shaanxi,China;Jingneng Group,Xilin Coal Limited Liability Company,Xilinguolemeng 026000,Inner Mongolia,China)

机构地区：[1]咸阳师范学院非线性科学研究所,陕西咸阳712000 [2]京能锡林煤化有限责任公司,内蒙古锡林郭勒盟026000

出　　处：《咸阳师范学院学报》2018年第4期30-34,共5页Journal of Xianyang Normal University

基　　金：陕西省教育厅科研基金项目(17JK0824)

摘　　要：探讨了一类时滞混杂神经网络模型的周期性问题。利用Lyapunov-Krasovskii能量函数稳定性分析方法,结合经典不等式、脉冲微分不等式和线性矩阵不等式,建立了两个具有脉冲扰动混杂神经网络系统的周期解指数稳定性的充分条件。A discussion was conducted of the periodicity problem for a class of delayed hybrid neural networks. Lyapunov-Krasovskii stability analytical methodology was developed for this system by combining stochastic analysis, classical inequalities and linear matrix inequality techniques. Two sufficient conditions were proposed to guarantee the globally exponentially periodic in the mean square sense of delayed neural networks with stochastic and impulsive perturbation.

关 键 词：时滞神经网络 脉冲 LYAPUNOV-KRASOVSKII泛函 周期性 

分 类 号：O231.2[理学—运筹学与控制论]