{"title":"时变时滞随机递归神经网络的稳定性分析","authors":"Nan Ding, Linshan Wang","doi":"10.1109/ICICIP.2012.6391486","DOIUrl":null,"url":null,"abstract":"In this paper, almost sure exponential stability of stochastic recurrent neural networks with time-varying delays was discussed. Without the differentiability of the delay functions, a new result to ensure the almost sure exponential stability of the system was obtained by using variation parameter approach and stochastic analysis.","PeriodicalId":376265,"journal":{"name":"2012 Third International Conference on Intelligent Control and Information Processing","volume":"6 16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stability analysis of stochastic recurrent neural networks with time-varying delays\",\"authors\":\"Nan Ding, Linshan Wang\",\"doi\":\"10.1109/ICICIP.2012.6391486\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, almost sure exponential stability of stochastic recurrent neural networks with time-varying delays was discussed. Without the differentiability of the delay functions, a new result to ensure the almost sure exponential stability of the system was obtained by using variation parameter approach and stochastic analysis.\",\"PeriodicalId\":376265,\"journal\":{\"name\":\"2012 Third International Conference on Intelligent Control and Information Processing\",\"volume\":\"6 16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Third International Conference on Intelligent Control and Information Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICIP.2012.6391486\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Third International Conference on Intelligent Control and Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICIP.2012.6391486","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stability analysis of stochastic recurrent neural networks with time-varying delays
In this paper, almost sure exponential stability of stochastic recurrent neural networks with time-varying delays was discussed. Without the differentiability of the delay functions, a new result to ensure the almost sure exponential stability of the system was obtained by using variation parameter approach and stochastic analysis.