{"title":"Stability analysis for a class of delay neural networks with nonlinear perturbations","authors":"Ruliang Wang, Hong Lei, Jin Wang","doi":"10.1109/ICCSE.2009.5228504","DOIUrl":null,"url":null,"abstract":"In this paper, we consider a class of time-delay dynamical neural networks with nonlinear perturbation. The nonlinear perturbation functions are assumed bounded. we derive a robust stability criterion independent of delay. The sufficient criterion is given in terms of linear matrix inequality (LMI). The checking for robust stability of time-delay dynamical neural networks with nonlinear perturbation by our result can be carried out rather simply, and convenient for the application. The applicability of our results is demonstrated by means of a specific example.","PeriodicalId":303484,"journal":{"name":"2009 4th International Conference on Computer Science & Education","volume":"241 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 4th International Conference on Computer Science & Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSE.2009.5228504","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, we consider a class of time-delay dynamical neural networks with nonlinear perturbation. The nonlinear perturbation functions are assumed bounded. we derive a robust stability criterion independent of delay. The sufficient criterion is given in terms of linear matrix inequality (LMI). The checking for robust stability of time-delay dynamical neural networks with nonlinear perturbation by our result can be carried out rather simply, and convenient for the application. The applicability of our results is demonstrated by means of a specific example.