{"title":"基于非约简方法的不连续模糊惯性神经网络定时投影同步","authors":"Yang Liu, Guodong Zhang","doi":"10.1109/icaci55529.2022.9837526","DOIUrl":null,"url":null,"abstract":"In this paper, fixed-time projective synchronization (FXTPS) of discontinuous fuzzy inertial neural networks (FINNs) is explored. A class of FINNs with discrete and bounded distributed time-varying delays is proposed. Based on this model, a non-reduced approach is utilized to design an effective feedback control scheme. And sufficient conditions for FXTPS are established. Finally, a numerical example is used to verify the validity of the theoretical results obtained.","PeriodicalId":412347,"journal":{"name":"2022 14th International Conference on Advanced Computational Intelligence (ICACI)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fixed-time Projective Synchronization For Discontinuous Fuzzy Inertial Neural Networks Via Non-reduced Method\",\"authors\":\"Yang Liu, Guodong Zhang\",\"doi\":\"10.1109/icaci55529.2022.9837526\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, fixed-time projective synchronization (FXTPS) of discontinuous fuzzy inertial neural networks (FINNs) is explored. A class of FINNs with discrete and bounded distributed time-varying delays is proposed. Based on this model, a non-reduced approach is utilized to design an effective feedback control scheme. And sufficient conditions for FXTPS are established. Finally, a numerical example is used to verify the validity of the theoretical results obtained.\",\"PeriodicalId\":412347,\"journal\":{\"name\":\"2022 14th International Conference on Advanced Computational Intelligence (ICACI)\",\"volume\":\"142 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 14th International Conference on Advanced Computational Intelligence (ICACI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/icaci55529.2022.9837526\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 14th International Conference on Advanced Computational Intelligence (ICACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icaci55529.2022.9837526","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fixed-time Projective Synchronization For Discontinuous Fuzzy Inertial Neural Networks Via Non-reduced Method
In this paper, fixed-time projective synchronization (FXTPS) of discontinuous fuzzy inertial neural networks (FINNs) is explored. A class of FINNs with discrete and bounded distributed time-varying delays is proposed. Based on this model, a non-reduced approach is utilized to design an effective feedback control scheme. And sufficient conditions for FXTPS are established. Finally, a numerical example is used to verify the validity of the theoretical results obtained.
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