{"title":"有无参数不确定性的多加权耦合神经网络有限时间拓扑辨识","authors":"Han-Yu Wu","doi":"10.1109/IHMSC52134.2021.00023","DOIUrl":null,"url":null,"abstract":"This paper mainly studies the problem of finite-time topology identification for multi-weighted coupled neural networks with and without parameter uncertainties. By designing the response networks, several parameter adjustment strategies and state feedback controllers, and making use of some inequality techniques, we identify the topology of original networks based on the synchronization property. Finally, an example is given to illustrate the effectiveness of the proposed finite-time topology identification criterion.","PeriodicalId":380011,"journal":{"name":"2021 13th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Finite-Time Topology Identification of Multi-weighted Coupled Neural Networks with and without Parameter Uncertainties\",\"authors\":\"Han-Yu Wu\",\"doi\":\"10.1109/IHMSC52134.2021.00023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper mainly studies the problem of finite-time topology identification for multi-weighted coupled neural networks with and without parameter uncertainties. By designing the response networks, several parameter adjustment strategies and state feedback controllers, and making use of some inequality techniques, we identify the topology of original networks based on the synchronization property. Finally, an example is given to illustrate the effectiveness of the proposed finite-time topology identification criterion.\",\"PeriodicalId\":380011,\"journal\":{\"name\":\"2021 13th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 13th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IHMSC52134.2021.00023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 13th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IHMSC52134.2021.00023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Finite-Time Topology Identification of Multi-weighted Coupled Neural Networks with and without Parameter Uncertainties
This paper mainly studies the problem of finite-time topology identification for multi-weighted coupled neural networks with and without parameter uncertainties. By designing the response networks, several parameter adjustment strategies and state feedback controllers, and making use of some inequality techniques, we identify the topology of original networks based on the synchronization property. Finally, an example is given to illustrate the effectiveness of the proposed finite-time topology identification criterion.