Leilei Li , Jingfeng Feng , Jianhui He , Jonathon A. Chambers
{"title":"A Distributed Variable Tap-length Algorithm within Diffusion Adaptive Networks","authors":"Leilei Li , Jingfeng Feng , Jianhui He , Jonathon A. Chambers","doi":"10.1016/j.aasri.2013.10.061","DOIUrl":null,"url":null,"abstract":"<div><p>In this work, an adaptive algorithm with variable tap-length is proposed for diffusion networks, where all nodes exchange information with their connected group without a fusion center and utilize both exchanged information and their local observation to make their individual estimations. Based on a fractional tap-length solution and the fully distributed structure of networks, we propose the algorithm to resolve the estimation problems on both tap-length and tap-weights. The proposed algorithm with adaptive tap-length structure enables the networks to reduce communication energy and network resources. The convergence properties of this algorithm are confirmed by the simulation results.</p></div>","PeriodicalId":100008,"journal":{"name":"AASRI Procedia","volume":"5 ","pages":"Pages 77-84"},"PeriodicalIF":0.0000,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.aasri.2013.10.061","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AASRI Procedia","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212671613000620","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this work, an adaptive algorithm with variable tap-length is proposed for diffusion networks, where all nodes exchange information with their connected group without a fusion center and utilize both exchanged information and their local observation to make their individual estimations. Based on a fractional tap-length solution and the fully distributed structure of networks, we propose the algorithm to resolve the estimation problems on both tap-length and tap-weights. The proposed algorithm with adaptive tap-length structure enables the networks to reduce communication energy and network resources. The convergence properties of this algorithm are confirmed by the simulation results.