{"title":"时变时滞hopfield神经网络的鲁棒稳定性新准则","authors":"Fang Liu, Yong He, Yong Li, M. Dong","doi":"10.1109/ICIEA.2017.8282941","DOIUrl":null,"url":null,"abstract":"This paper investigates the robust stability problem of Hopfield neural networks(HNNs) with time-varying delay. Two novel LMI-based delay-dependent robust stability criteria are obtained by constructing appropriate Lyapunov-Krasovskii functional. This new criteria based on the free-weighting matrices approach prove to be less conservativeness, which not only retain any useful terms in the derivative of Lyapunov-Krasovskii functional, but also consider the relationship among the time-delay, its upper bound and their difference. Finally, some numerical examples are given to demonstrate its merits and effectiveness of the proposed methods.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Novel delay-dependent robust stability criteria of hopfield neural networks with time-varying delay\",\"authors\":\"Fang Liu, Yong He, Yong Li, M. Dong\",\"doi\":\"10.1109/ICIEA.2017.8282941\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates the robust stability problem of Hopfield neural networks(HNNs) with time-varying delay. Two novel LMI-based delay-dependent robust stability criteria are obtained by constructing appropriate Lyapunov-Krasovskii functional. This new criteria based on the free-weighting matrices approach prove to be less conservativeness, which not only retain any useful terms in the derivative of Lyapunov-Krasovskii functional, but also consider the relationship among the time-delay, its upper bound and their difference. Finally, some numerical examples are given to demonstrate its merits and effectiveness of the proposed methods.\",\"PeriodicalId\":443463,\"journal\":{\"name\":\"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIEA.2017.8282941\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIEA.2017.8282941","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Novel delay-dependent robust stability criteria of hopfield neural networks with time-varying delay
This paper investigates the robust stability problem of Hopfield neural networks(HNNs) with time-varying delay. Two novel LMI-based delay-dependent robust stability criteria are obtained by constructing appropriate Lyapunov-Krasovskii functional. This new criteria based on the free-weighting matrices approach prove to be less conservativeness, which not only retain any useful terms in the derivative of Lyapunov-Krasovskii functional, but also consider the relationship among the time-delay, its upper bound and their difference. Finally, some numerical examples are given to demonstrate its merits and effectiveness of the proposed methods.