{"title":"一种估计多智能体网络代数连通性的分散离散时间算法","authors":"Kento Endo, Norikazu Takahashi","doi":"10.1109/APCCAS.2016.7803941","DOIUrl":null,"url":null,"abstract":"Algebraic connectivity of a network, which is defined as the second smallest eigenvalue of the Laplacian matrix, represents how strongly the network is connected. This paper proposes a new decentralized discrete-time algorithm for the estimation of the algebraic connectivity of multiagent networks. The validity of the proposed algorithm is verified by theoretical analysis and numerical experiments.","PeriodicalId":6495,"journal":{"name":"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"A new decentralized discrete-time algorithm for estimating algebraic connectivity of multiagent networks\",\"authors\":\"Kento Endo, Norikazu Takahashi\",\"doi\":\"10.1109/APCCAS.2016.7803941\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Algebraic connectivity of a network, which is defined as the second smallest eigenvalue of the Laplacian matrix, represents how strongly the network is connected. This paper proposes a new decentralized discrete-time algorithm for the estimation of the algebraic connectivity of multiagent networks. The validity of the proposed algorithm is verified by theoretical analysis and numerical experiments.\",\"PeriodicalId\":6495,\"journal\":{\"name\":\"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APCCAS.2016.7803941\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCCAS.2016.7803941","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new decentralized discrete-time algorithm for estimating algebraic connectivity of multiagent networks
Algebraic connectivity of a network, which is defined as the second smallest eigenvalue of the Laplacian matrix, represents how strongly the network is connected. This paper proposes a new decentralized discrete-time algorithm for the estimation of the algebraic connectivity of multiagent networks. The validity of the proposed algorithm is verified by theoretical analysis and numerical experiments.