Event-Based Synchronization for Multiple Neural Networks With Time Delay and Switching Disconnected Topology

被引：23

作者：

Chen, Jiejie ^{[1
,2
]}

Chen, Boshan ^{[3
]}

Zeng, Zhigang ^{[2
,4
]}

Jiang, Ping ^{[5
]}

机构：

[1] Hubei Normal Univ, Sch Comp & Informat Engn, Huangshi 435002, Hubei, Peoples R China

[2] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Peoples R China

[3] Hubei Normal Univ, Coll Math & Stat, Huangshi 435002, Hubei, Peoples R China

[4] Educ Minist China, Key Lab Image Proc & Intelligent Control, Wuhan 430074, Peoples R China

[5] Hubei PolyTech Univ, Comp Sch, Huangshi 435002, Hubei, Peoples R China

来源：

IEEE TRANSACTIONS ON CYBERNETICS | 2021年 / 51卷 / 12期

关键词：

Topology; Switches; Synchronization; Network topology; Artificial neural networks; Delays; Protocols; Event-triggered; multiple neural networks (MNNs); quasisynchronization; switching topology; synchronization; 2ND-ORDER MULTIAGENT SYSTEMS; EXPONENTIAL SYNCHRONIZATION; GLOBAL SYNCHRONIZATION; DYNAMICAL NETWORKS; CONSENSUS; STABILITY;

D O I：

10.1109/TCYB.2019.2960762

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This article discusses the synchronization problem for a class of multiple delayed neural networks (MDNNs) with a directed switching topology by using an event-triggering strategy. First, a new differential inequality with delay is shown, which is a generalization of Halanay-type inequalities. Then, the sufficient conditions of event-based synchronization (quasisynchronization) for MDNN with sequentially connected topology are obtained by using this inequality and the iterative method. Meantime, we prove that Zeno behavior can be avoided under the designed event-triggering rules. As an extension, MDNN with jointly connected topology is also discussed. Finally, a numerical example is listed to illustrate the results in theory analysis.

引用

页码：5993 / 6003

页数：11

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