{"title":"时滞惯性神经网络镇定的脉冲控制方法","authors":"K. R","doi":"10.4108/eai.7-12-2021.2315115","DOIUrl":null,"url":null,"abstract":": Stabilization of delayed inertial neural networks based on impulsesl is investigated in this paper. Delay-dependent sufficient conditions of stabilization results are obtained as linear matrix inequalities via Lyapunov stability theory which involves the construction of Lyapunov-Krasovskii functional. Information of time-delay is taken into account to obtain these results. Here, time-delay is considered to be time-varying and the activation function is assumed to be sector bounded. Derived conditions can be validated via MATLAB. Finally, an example is provided to support the derived results.","PeriodicalId":20712,"journal":{"name":"Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Impulsive Control Approach to Stabilization of Delayed Inertial Neural Networks\",\"authors\":\"K. R\",\"doi\":\"10.4108/eai.7-12-2021.2315115\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": Stabilization of delayed inertial neural networks based on impulsesl is investigated in this paper. Delay-dependent sufficient conditions of stabilization results are obtained as linear matrix inequalities via Lyapunov stability theory which involves the construction of Lyapunov-Krasovskii functional. Information of time-delay is taken into account to obtain these results. Here, time-delay is considered to be time-varying and the activation function is assumed to be sector bounded. Derived conditions can be validated via MATLAB. Finally, an example is provided to support the derived results.\",\"PeriodicalId\":20712,\"journal\":{\"name\":\"Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4108/eai.7-12-2021.2315115\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4108/eai.7-12-2021.2315115","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Impulsive Control Approach to Stabilization of Delayed Inertial Neural Networks
: Stabilization of delayed inertial neural networks based on impulsesl is investigated in this paper. Delay-dependent sufficient conditions of stabilization results are obtained as linear matrix inequalities via Lyapunov stability theory which involves the construction of Lyapunov-Krasovskii functional. Information of time-delay is taken into account to obtain these results. Here, time-delay is considered to be time-varying and the activation function is assumed to be sector bounded. Derived conditions can be validated via MATLAB. Finally, an example is provided to support the derived results.
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