具有马尔可夫跳变参数的不确定时滞模糊Hopfield神经网络的鲁棒稳定性。

Hongyi Li, Bing Chen, Qi Zhou, Weiyi Qian
{"title":"具有马尔可夫跳变参数的不确定时滞模糊Hopfield神经网络的鲁棒稳定性。","authors":"Hongyi Li,&nbsp;Bing Chen,&nbsp;Qi Zhou,&nbsp;Weiyi Qian","doi":"10.1109/TSMCB.2008.2002812","DOIUrl":null,"url":null,"abstract":"<p><p>This paper is concerned with the problem of the robust stability of nonlinear delayed Hopfield neural networks (HNNs) with Markovian jumping parameters by Takagi-Sugeno (T-S) fuzzy model. The nonlinear delayed HNNs are first established as a modified T-S fuzzy model in which the consequent parts are composed of a set of Markovian jumping HNNs with interval delays. Time delays here are assumed to be time-varying and belong to the given intervals. Based on Lyapunov-Krasovskii stability theory and linear matrix inequality approach, stability conditions are proposed in terms of the upper and lower bounds of the delays. Finally, numerical examples are used to illustrate the effectiveness of the proposed method.</p>","PeriodicalId":55006,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","volume":" ","pages":"94-102"},"PeriodicalIF":0.0000,"publicationDate":"2009-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TSMCB.2008.2002812","citationCount":"310","resultStr":"{\"title\":\"Robust stability for uncertain delayed fuzzy Hopfield neural networks with Markovian jumping parameters.\",\"authors\":\"Hongyi Li,&nbsp;Bing Chen,&nbsp;Qi Zhou,&nbsp;Weiyi Qian\",\"doi\":\"10.1109/TSMCB.2008.2002812\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This paper is concerned with the problem of the robust stability of nonlinear delayed Hopfield neural networks (HNNs) with Markovian jumping parameters by Takagi-Sugeno (T-S) fuzzy model. The nonlinear delayed HNNs are first established as a modified T-S fuzzy model in which the consequent parts are composed of a set of Markovian jumping HNNs with interval delays. Time delays here are assumed to be time-varying and belong to the given intervals. Based on Lyapunov-Krasovskii stability theory and linear matrix inequality approach, stability conditions are proposed in terms of the upper and lower bounds of the delays. Finally, numerical examples are used to illustrate the effectiveness of the proposed method.</p>\",\"PeriodicalId\":55006,\"journal\":{\"name\":\"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics\",\"volume\":\" \",\"pages\":\"94-102\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/TSMCB.2008.2002812\",\"citationCount\":\"310\",\"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.2008.2002812\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TSMCB.2008.2002812","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 310

摘要

利用Takagi-Sugeno (T-S)模糊模型研究具有马尔可夫跳变参数的非线性时滞Hopfield神经网络的鲁棒稳定性问题。首先将非线性延迟hnn建立为一个改进的T-S模糊模型,其中后部分由一组具有区间延迟的马尔可夫跳变hnn组成。这里假定时滞是时变的,属于给定的区间。基于Lyapunov-Krasovskii稳定性理论和线性矩阵不等式方法,给出了时滞上界和下界的稳定性条件。最后,通过数值算例验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust stability for uncertain delayed fuzzy Hopfield neural networks with Markovian jumping parameters.

This paper is concerned with the problem of the robust stability of nonlinear delayed Hopfield neural networks (HNNs) with Markovian jumping parameters by Takagi-Sugeno (T-S) fuzzy model. The nonlinear delayed HNNs are first established as a modified T-S fuzzy model in which the consequent parts are composed of a set of Markovian jumping HNNs with interval delays. Time delays here are assumed to be time-varying and belong to the given intervals. Based on Lyapunov-Krasovskii stability theory and linear matrix inequality approach, stability conditions are proposed in terms of the upper and lower bounds of the delays. Finally, numerical examples are used to illustrate the effectiveness of the proposed method.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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