{"title":"基于LMI的延迟混沌神经网络同步","authors":"R. Wu, Weiwei Zhang","doi":"10.1109/FGCNS.2008.117","DOIUrl":null,"url":null,"abstract":"In the current paper, exponential synchronization is discussed for chaotic neural networks with time-varying delays. Based on Lyapunov stability theory and linear matrix inequality (LMI), a nonlinear feedback control scheme is designed to synchronize the drive system and the response one. The obtained sufficient conditions are in the forms of LMI, so much easier to verify. Moreover, numerical simulation shows the effectiveness of this nonlinear control scheme.","PeriodicalId":370780,"journal":{"name":"2008 Second International Conference on Future Generation Communication and Networking Symposia","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Synchronization of Delayed Chaotic Neural Networks by LMI\",\"authors\":\"R. Wu, Weiwei Zhang\",\"doi\":\"10.1109/FGCNS.2008.117\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the current paper, exponential synchronization is discussed for chaotic neural networks with time-varying delays. Based on Lyapunov stability theory and linear matrix inequality (LMI), a nonlinear feedback control scheme is designed to synchronize the drive system and the response one. The obtained sufficient conditions are in the forms of LMI, so much easier to verify. Moreover, numerical simulation shows the effectiveness of this nonlinear control scheme.\",\"PeriodicalId\":370780,\"journal\":{\"name\":\"2008 Second International Conference on Future Generation Communication and Networking Symposia\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Second International Conference on Future Generation Communication and Networking Symposia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FGCNS.2008.117\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Second International Conference on Future Generation Communication and Networking Symposia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FGCNS.2008.117","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Synchronization of Delayed Chaotic Neural Networks by LMI
In the current paper, exponential synchronization is discussed for chaotic neural networks with time-varying delays. Based on Lyapunov stability theory and linear matrix inequality (LMI), a nonlinear feedback control scheme is designed to synchronize the drive system and the response one. The obtained sufficient conditions are in the forms of LMI, so much easier to verify. Moreover, numerical simulation shows the effectiveness of this nonlinear control scheme.
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