中南大学学报（自然科学版）2018，Vol.49Issue(6)：1432-1439,8.DOI:10.11817/j.issn.1672-7207.2018.06.016
具有混合时变时滞主从神经网络的指数采样同步控制
Sampled-data exponential synchronization of master-slave neural networks with time-varying mixed delays
摘要
Abstract
Sampled-data exponential synchronization problems for master-slave neural networks with time-varying mixed delays were investigated with the Lyapunov-Krasovskii functional approach and linear matrix inequality(LMI).By constructing the novel Lyapunov-Krasovskii functions and estimating the derivative of them with a set of inequality methods, exponential synchronization criteria with time-varying delays were derived, which had less conservative. Then, depending upon the maximum sampling interval and decay rate, the desired sampled-data controller was achieved. The numerical example and simulation results verify the superiority and effectiveness of the approach.关键词
主从神经网络/Lyapunov-Krasovskii泛函/指数采样同步控制Key words
master-slave neural networks/Lyapunov-Krasovskii function/sampled-data exponential synchronization分类
信息技术与安全科学引用本文复制引用
陈刚,王信,肖伸平,杜博文,王聪聪,罗昌胜..具有混合时变时滞主从神经网络的指数采样同步控制[J].中南大学学报（自然科学版）,2018,49(6):1432-1439,8.基金项目
湖南省自然科学基金项目(2018JJ4075) （2018JJ4075）
国家自然科学基金资助项目(61672225,61304064)(Project(2018JJ4075) supported by the Natural Science Foundation of Hunan Province （61672225,61304064）
Projects(61672225, 61304064) supported by the National Natural Science Foundation of China) （61672225, 61304064）
