{"title":"一类新的时滞Hopfield神经网络全局稳定性判据","authors":"Degang Yang, Qun Liu, Yong Wang","doi":"10.1109/GrC.2007.16","DOIUrl":null,"url":null,"abstract":"This paper analyzes the global asymptotic stability of delayed Hopfield neural networks by utilizing Lyapunov functional method and a generalized inequality technique. A new sufficient condition ensuring global asymptotic stability of the unique equilibrium point of delayed Hopfield neural networks is obtained. The result is related to the size of delays. The obtained conditions show to be less conservative and restrictive than that reported in the literature. A numerical simulation is given to illustrate the efficiency of our result.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Novel Delay-Dependent Global Stability Criterion of Delayed Hopfield Neural Networks\",\"authors\":\"Degang Yang, Qun Liu, Yong Wang\",\"doi\":\"10.1109/GrC.2007.16\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper analyzes the global asymptotic stability of delayed Hopfield neural networks by utilizing Lyapunov functional method and a generalized inequality technique. A new sufficient condition ensuring global asymptotic stability of the unique equilibrium point of delayed Hopfield neural networks is obtained. The result is related to the size of delays. The obtained conditions show to be less conservative and restrictive than that reported in the literature. A numerical simulation is given to illustrate the efficiency of our result.\",\"PeriodicalId\":259430,\"journal\":{\"name\":\"2007 IEEE International Conference on Granular Computing (GRC 2007)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE International Conference on Granular Computing (GRC 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GrC.2007.16\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Conference on Granular Computing (GRC 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GrC.2007.16","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Delay-Dependent Global Stability Criterion of Delayed Hopfield Neural Networks
This paper analyzes the global asymptotic stability of delayed Hopfield neural networks by utilizing Lyapunov functional method and a generalized inequality technique. A new sufficient condition ensuring global asymptotic stability of the unique equilibrium point of delayed Hopfield neural networks is obtained. The result is related to the size of delays. The obtained conditions show to be less conservative and restrictive than that reported in the literature. A numerical simulation is given to illustrate the efficiency of our result.
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