{"title":"时滞随机区间细胞神经网络的指数稳定性","authors":"Jinfang Han, Fachao Li","doi":"10.1109/ICWAPR.2009.5207427","DOIUrl":null,"url":null,"abstract":"In this paper, the exponential stability problem of a class of stochastic interval delayed cellular neural networks is studied. Firstly, a kind of equivalent description of this stochastic interval delayed cellular neural networks is presented. Then by using the Itô formula, Razumikhin theorems, Lyapunov function and norm inequalities, several simple sufficient conditions are obtained which guarantee the exponential stability of the stochastic interval cellular neural networks. and some recent results reported in the literature are generalized.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"525 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exponential stability of stochastic interval cellular neural networks with delays\",\"authors\":\"Jinfang Han, Fachao Li\",\"doi\":\"10.1109/ICWAPR.2009.5207427\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the exponential stability problem of a class of stochastic interval delayed cellular neural networks is studied. Firstly, a kind of equivalent description of this stochastic interval delayed cellular neural networks is presented. Then by using the Itô formula, Razumikhin theorems, Lyapunov function and norm inequalities, several simple sufficient conditions are obtained which guarantee the exponential stability of the stochastic interval cellular neural networks. and some recent results reported in the literature are generalized.\",\"PeriodicalId\":424264,\"journal\":{\"name\":\"2009 International Conference on Wavelet Analysis and Pattern Recognition\",\"volume\":\"525 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Wavelet Analysis and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICWAPR.2009.5207427\",\"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 International Conference on Wavelet Analysis and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWAPR.2009.5207427","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Exponential stability of stochastic interval cellular neural networks with delays
In this paper, the exponential stability problem of a class of stochastic interval delayed cellular neural networks is studied. Firstly, a kind of equivalent description of this stochastic interval delayed cellular neural networks is presented. Then by using the Itô formula, Razumikhin theorems, Lyapunov function and norm inequalities, several simple sufficient conditions are obtained which guarantee the exponential stability of the stochastic interval cellular neural networks. and some recent results reported in the literature are generalized.