Asymptotic Bipartite Synchronization of Coupled Neural Networks Via Quantized Control

Ting Liu, Junhong Zhao, Peng Liu, Jian Yong, Shulong Fan, Junwei Sun
{"title":"Asymptotic Bipartite Synchronization of Coupled Neural Networks Via Quantized Control","authors":"Ting Liu, Junhong Zhao, Peng Liu, Jian Yong, Shulong Fan, Junwei Sun","doi":"10.1109/icaci55529.2022.9837729","DOIUrl":null,"url":null,"abstract":"This paper addresses the bipartite synchronization of coupled neural networks with time-varying delay. By introducing an effective quantized controller, the bipartite synchronization of coupled neural networks with time-varying delay is realized and sufficient conditions for assuring the bipartite synchronization are derived in virtue of a Halanay inequality. Moreover, the bipartite synchronization of coupled neural networks without delay via quantized controller is also taken into account in corollary as a special case. In the end, a numerical example is provided to demonstrate the correctness of theoretical results.","PeriodicalId":412347,"journal":{"name":"2022 14th International Conference on Advanced Computational Intelligence (ICACI)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 14th International Conference on Advanced Computational Intelligence (ICACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icaci55529.2022.9837729","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This paper addresses the bipartite synchronization of coupled neural networks with time-varying delay. By introducing an effective quantized controller, the bipartite synchronization of coupled neural networks with time-varying delay is realized and sufficient conditions for assuring the bipartite synchronization are derived in virtue of a Halanay inequality. Moreover, the bipartite synchronization of coupled neural networks without delay via quantized controller is also taken into account in corollary as a special case. In the end, a numerical example is provided to demonstrate the correctness of theoretical results.
基于量化控制的耦合神经网络渐近二部同步
研究了时变时滞耦合神经网络的二部同步问题。通过引入有效的量化控制器,实现了时变时滞耦合神经网络的二部同步,并利用Halanay不等式导出了保证二部同步的充分条件。此外,作为一种特例,在推论中还考虑了通过量化控制器实现无延迟耦合神经网络的二部同步。最后,通过数值算例验证了理论结果的正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信