On Hybrid Impulsive and Switching Neural Networks

Chuandong Li, G. Feng, Tingwen Huang
{"title":"On Hybrid Impulsive and Switching Neural Networks","authors":"Chuandong Li, G. Feng, Tingwen Huang","doi":"10.1109/TSMCB.2008.928233","DOIUrl":null,"url":null,"abstract":"This paper formulates and studies a model of hybrid impulsive and switching Hopfield neural networks (NNs). Using switching Lyapunov functions and a generalized Halanay inequality, some general criteria, which characterize the impulse and switching effects in aggregated form, for asymptotic and exponential stability of such NNs with arbitrary and conditioned impulsive switching are established. Several numerical examples are given for illustration and interpretation of the theoretical results.","PeriodicalId":55006,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","volume":"214 1","pages":"1549-1560"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"104","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TSMCB.2008.928233","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 104

Abstract

This paper formulates and studies a model of hybrid impulsive and switching Hopfield neural networks (NNs). Using switching Lyapunov functions and a generalized Halanay inequality, some general criteria, which characterize the impulse and switching effects in aggregated form, for asymptotic and exponential stability of such NNs with arbitrary and conditioned impulsive switching are established. Several numerical examples are given for illustration and interpretation of the theoretical results.
混合脉冲和切换神经网络
本文建立并研究了一种脉冲和开关混合Hopfield神经网络模型。利用切换Lyapunov函数和广义Halanay不等式,建立了具有任意条件脉冲切换的神经网络的渐近稳定性和指数稳定性的一般准则,以聚合形式描述了脉冲和切换效应。给出了几个数值算例来说明和解释理论结果。
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
审稿时长
6.0 months
×
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