带马氏切换的时滞脉冲神经网络稳定性分析  

The Stability of Impulsive Stochastic Delay Neural Networks with Markovian Switching

作　　者：席福宝 徐畅 XI Fu-bao;XU Chang(School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China)

机构地区：[1]北京理工大学数学与统计学院,北京100081

出　　处：《北京理工大学学报》2020年第10期1133-1137,共5页Transactions of Beijing Institute of Technology

基　　金：国家自然科学基金资助项目(11671034)。

摘　　要：为研究带马氏切换的时滞脉冲随机神经网络的均方指数稳定性,构造了合适的Lyapunov函数,并利用伊藤公式、矩阵知识、泛函理论及神经网络自身的特性,对脉冲时刻及非脉冲时刻的系统状态进行分析,得到了该神经网络具有均方指数稳定性的判别准则,该准则应用广泛,简单好用.最后通过数值例子及仿真模拟,说明了该准则的正确性.In order to study the mean square exponential stability of impulse stochastic delay neural networks with Markovian switching,a suitable Lyapunov function was established.Based on Ito^formula,functional theory,the characteristics of neural networks and the knowledge of matrix,the state of system at impulsive time and non-impulsive time was analyzed,getting the rules to distinguish the mean square exponential stability of the stochastic neural network.The numerical example analysis and simulation results show that the rules are efficient,simple and validity.

关 键 词：时滞脉冲神经网络 均方指数稳定性 马氏切换 

分 类 号：O175[理学—数学]