文献类型：期刊文献

英文题名：Dynamic Event-Triggered Stabilization for Markov Jump Delayed Complex-Valued Neural Networks

作者：Wang, Yuan[1]; Yan, Huaicheng[1,2]; Xue, Min[1]; Wang, Meng[1]; Zhou, Jing[3]

机构：[1] Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, 200237, China; [2] School of Information Science and Engineering, Chengdu University, Chengdu, 610106, China; [3] School of Artificial Intelligence, Jianghan University, Hubei, Wuhan, 430056, China

年份：2021

起止页码：8295

外文期刊名：Proceeding - 2021 China Automation Congress, CAC 2021

收录：EI(收录号：20221611968596)

语种：英文

外文关键词：Complex networks - Markov processes - Stability criteria

摘要：The paper addresses the problem of stabilization for Markov jump complex-valued neural networks with time-varying delays. The Markov model is adopted to describe the abrupt changes in the parameters of system. In order to make better use of the limited network bandwidth, a novel dynamic event-triggered scheme (DETS) is developed to schedule the data transmission. Based on the Lyapunov stability theory, the delay-dependent stability criterion is presented. Finally, the simulation results are given to verify the usefulness of the proposed stabilizing method. ? 2021 IEEE