{"title":"时滞细胞神经网络的一个新的全局渐近稳定性结果","authors":"Jing Liu, Ce Zhang","doi":"10.1109/CCDC.2009.5192532","DOIUrl":null,"url":null,"abstract":"This paper studies the problem of global asymptotic stability for delayed cellular neural networks(DCNNs). A new stability condition is obtained by utilizing the Lyapunov functional method and the matrix inequality approach. This condition is less restrictive and generalizes some of the previous stability results derived in the literature.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new global asymptotic stability result for delayed cellular neural networks\",\"authors\":\"Jing Liu, Ce Zhang\",\"doi\":\"10.1109/CCDC.2009.5192532\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper studies the problem of global asymptotic stability for delayed cellular neural networks(DCNNs). A new stability condition is obtained by utilizing the Lyapunov functional method and the matrix inequality approach. This condition is less restrictive and generalizes some of the previous stability results derived in the literature.\",\"PeriodicalId\":127110,\"journal\":{\"name\":\"2009 Chinese Control and Decision Conference\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Chinese Control and Decision Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCDC.2009.5192532\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Chinese Control and Decision Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2009.5192532","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new global asymptotic stability result for delayed cellular neural networks
This paper studies the problem of global asymptotic stability for delayed cellular neural networks(DCNNs). A new stability condition is obtained by utilizing the Lyapunov functional method and the matrix inequality approach. This condition is less restrictive and generalizes some of the previous stability results derived in the literature.
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