論文

2018年9月10日

An Adaptive Combination Rule for Diffusion LMS Based on Consensus Propagation

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
  • Ayano Nakai
  • ,
  • Kazunori Hayashi

2018-April
開始ページ
3839
終了ページ
3843
記述言語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1109/ICASSP.2018.8462277
出版者・発行元
IEEE

Diffusion least-mean-square (LMS) algorithm is a method that estimates an unknown global vector from its linear measurements obtained at multiple nodes in a network in a distributed manner. This paper proposes a novel combination rule in the algorithm used to integrate the local estimates at each node by using the idea of consensus propagation, which is known to be a fast algorithm to achieve the average consensus. Moreover, we optimize constants involved in the proposed combination rule in terms of the steady state mean-square-deviation (MSD) and show an adaptive combination rule, along with an adaptive implementation. Simulation results demonstrate that the proposed combination scheme achieves better MSD performance than conventional combination schemes.

リンク情報
DOI
https://doi.org/10.1109/ICASSP.2018.8462277
DBLP
https://dblp.uni-trier.de/rec/conf/icassp/NakaiH18
Scopus
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85054208552&origin=inward
Scopus Citedby
https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85054208552&origin=inward
URL
https://dblp.uni-trier.de/conf/icassp/2018
URL
https://dblp.uni-trier.de/db/conf/icassp/icassp2018.html#NakaiH18
ID情報
  • DOI : 10.1109/ICASSP.2018.8462277
  • ISSN : 1520-6149
  • DBLP ID : conf/icassp/NakaiH18
  • SCOPUS ID : 85054208552

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