{"title":"混合时滞中性型神经网络的鲁棒稳定性","authors":"Qingyu Zhu, Wuneng Zhou, Xiaozheng Mou","doi":"10.1109/WCICA.2010.5554143","DOIUrl":null,"url":null,"abstract":"In this paper, the robust stability is investigated for neural networks of neutral-type with both discrete and distributed time-varying delays. Based on Lyapunov-Krasovskii stability theory and stochastic analysis approaches, several new criteria are derived to guarantee the robust stability of the system. Some numerical examples are given to demonstrate the applicability of our proposed stability criteria.","PeriodicalId":315420,"journal":{"name":"2010 8th World Congress on Intelligent Control and Automation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust stability for neural networks of neutral-type with mixed time-delays\",\"authors\":\"Qingyu Zhu, Wuneng Zhou, Xiaozheng Mou\",\"doi\":\"10.1109/WCICA.2010.5554143\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the robust stability is investigated for neural networks of neutral-type with both discrete and distributed time-varying delays. Based on Lyapunov-Krasovskii stability theory and stochastic analysis approaches, several new criteria are derived to guarantee the robust stability of the system. Some numerical examples are given to demonstrate the applicability of our proposed stability criteria.\",\"PeriodicalId\":315420,\"journal\":{\"name\":\"2010 8th World Congress on Intelligent Control and Automation\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 8th World Congress on Intelligent Control and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCICA.2010.5554143\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 8th World Congress on Intelligent Control and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCICA.2010.5554143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Robust stability for neural networks of neutral-type with mixed time-delays
In this paper, the robust stability is investigated for neural networks of neutral-type with both discrete and distributed time-varying delays. Based on Lyapunov-Krasovskii stability theory and stochastic analysis approaches, several new criteria are derived to guarantee the robust stability of the system. Some numerical examples are given to demonstrate the applicability of our proposed stability criteria.
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