{"title":"不确定分数阶四元数神经网络的鲁棒定时同步","authors":"Zhongwen Wu","doi":"10.23919/SICEISCS54350.2022.9754525","DOIUrl":null,"url":null,"abstract":"In this article, the robust fixed-time synchronization of uncertain fractional-order quaternion-valued neural networks(FQVNNs) is studied. By using direct analytical method and quaternion-valued inequality, a criterion for robust fixed-time synchronization is established, and the settling time for robust fixed-time synchronization is explicitly reckoned. Finally, the validity of the conclusions is illustrated via one numerical example.","PeriodicalId":391189,"journal":{"name":"2022 SICE International Symposium on Control Systems (SICE ISCS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust fixed-time synchronization of uncertain fractional-order quaternion-valued neural networks\",\"authors\":\"Zhongwen Wu\",\"doi\":\"10.23919/SICEISCS54350.2022.9754525\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article, the robust fixed-time synchronization of uncertain fractional-order quaternion-valued neural networks(FQVNNs) is studied. By using direct analytical method and quaternion-valued inequality, a criterion for robust fixed-time synchronization is established, and the settling time for robust fixed-time synchronization is explicitly reckoned. Finally, the validity of the conclusions is illustrated via one numerical example.\",\"PeriodicalId\":391189,\"journal\":{\"name\":\"2022 SICE International Symposium on Control Systems (SICE ISCS)\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 SICE International Symposium on Control Systems (SICE ISCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/SICEISCS54350.2022.9754525\",\"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 SICE International Symposium on Control Systems (SICE ISCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/SICEISCS54350.2022.9754525","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Robust fixed-time synchronization of uncertain fractional-order quaternion-valued neural networks
In this article, the robust fixed-time synchronization of uncertain fractional-order quaternion-valued neural networks(FQVNNs) is studied. By using direct analytical method and quaternion-valued inequality, a criterion for robust fixed-time synchronization is established, and the settling time for robust fixed-time synchronization is explicitly reckoned. Finally, the validity of the conclusions is illustrated via one numerical example.