Finite-time Synchronization of Delayed Semi-Markov Neural Networks with Dynamic Event-triggered Scheme

被引：0
作者：
Yujing Jin
Wenhai Qi
Guangdeng Zong
机构：
[1] Qufu Normal University,School of Engineering
[2] Chengdu University,School of Information Science and Engineering
来源：
International Journal of Control, Automation and Systems | 2021年 / 19卷
关键词：
Dynamic event-triggered scheme; finite-time synchronization; Lyapunov-Krasovskii functional; semi-Markov neural networks;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, the finite-time synchronization (FTS) of semi-Markov neural networks (S-MNNs) with time-varying delay is presented. According to the Lyapunov stability theory, a mode-dependent Lyapunov-Krasovskii functional (LKF) is constructed. Compared with the traditional static event triggered scheme (ETS), a dynamic ETS is adopted to adjust the amount of data transmission and reduce the network burden. By using the general free-weighting matrix method (F-WMM) to estimate a single integral term, a less conservative conclusion is proposed in standard linear matrix inequalities (LMIs). Finally, under the comparison of the static ETS and the dynamic ETS, a simulation example verifies the superiority of this method.
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页码：2297 / 2308
页数：11
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