{"title":"New LMI-based criteria for global robust stability of neural networks with time-varying delays","authors":"Zhenhua Huang, B. Li","doi":"10.1109/ICACI.2012.6463197","DOIUrl":null,"url":null,"abstract":"In this paper, some sufficient conditions for global robust asymptotical stability of neural networks with time-varying delays are presented. On basis of the obtained results, some linear matrix inequality (LMI) criteria are derived. A comparison of the present criteria with the previous criteria is made. Moreover, an example is given to show the effectiveness of the obtained results.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACI.2012.6463197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, some sufficient conditions for global robust asymptotical stability of neural networks with time-varying delays are presented. On basis of the obtained results, some linear matrix inequality (LMI) criteria are derived. A comparison of the present criteria with the previous criteria is made. Moreover, an example is given to show the effectiveness of the obtained results.