Gossip BCLMS method over multi-agent networks

Jinli Yang*, Lijuan Jia, Cheng Ma, Lu Fan, Shunshoku Kanae

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

We study the problem of parameter estimation over multi-agent networks, where all nodes are corrupted by both input and output noise. A series of BCLMS algorithms based on diffusion strategies have been proposed, which modify the estimates while increase the communication resources. In this paper, We propose a gossip BCLMS algorithm, which can alleviate the communication pressure by reducing the interaction with the surrounding nodes and improve estimation performance of the network. The simulation results have confirmed the effectiveness of the proposed algorithm.

Original languageEnglish
Title of host publicationProceedings of the 38th Chinese Control Conference, CCC 2019
EditorsMinyue Fu, Jian Sun
PublisherIEEE Computer Society
Pages3703-3707
Number of pages5
ISBN (Electronic)9789881563972
DOIs
Publication statusPublished - Jul 2019
Event38th Chinese Control Conference, CCC 2019 - Guangzhou, China
Duration: 27 Jul 201930 Jul 2019

Publication series

NameChinese Control Conference, CCC
Volume2019-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference38th Chinese Control Conference, CCC 2019
Country/TerritoryChina
CityGuangzhou
Period27/07/1930/07/19

Keywords

  • Bias-compensated Method
  • Communication Resources
  • Gossip Strategy
  • Parameter Estimation

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