A novel adaptive algorithm for diffusion networks using projections onto hyperslabs

S. Chouvardas, K. Slavakis, S. Theodoridis
{"title":"A novel adaptive algorithm for diffusion networks using projections onto hyperslabs","authors":"S. Chouvardas, K. Slavakis, S. Theodoridis","doi":"10.1109/CIP.2010.5604244","DOIUrl":null,"url":null,"abstract":"In this paper, a new algorithm for distributed learning in sensor networks is developed. The algorithm is built upon a diffusion protocol to implement cooperation among neighbouring nodes. The algorithm is developed in the convex set theoretic approach, and it is based on a sequence of metric projections on hyperslabs. Full convergence results have been obtained and the experimental set up demonstrates significant performance improvements, compared to previously derived algorithms of similar complexity.","PeriodicalId":171474,"journal":{"name":"2010 2nd International Workshop on Cognitive Information Processing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd International Workshop on Cognitive Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIP.2010.5604244","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

In this paper, a new algorithm for distributed learning in sensor networks is developed. The algorithm is built upon a diffusion protocol to implement cooperation among neighbouring nodes. The algorithm is developed in the convex set theoretic approach, and it is based on a sequence of metric projections on hyperslabs. Full convergence results have been obtained and the experimental set up demonstrates significant performance improvements, compared to previously derived algorithms of similar complexity.
一种基于超实验室投影的扩散网络自适应算法
本文提出了一种新的传感器网络分布式学习算法。该算法建立在扩散协议的基础上,实现相邻节点之间的协作。该算法是在凸集理论的基础上发展起来的,它基于超实验室上的一系列度量投影。与先前导出的类似复杂度的算法相比,得到了完全收敛的结果,并且实验设置显示了显着的性能改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信