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Transient Analysis of Diffusion Recursive Least Squares via Signed Error Algorithm for Cyclostationary Colored Inputs

  • Wei Gao
  • , Yi Xu
  • , Jie Chen
  • , Cedric Richard
  • Jiangsu University
  • Université Côte d'Azur

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

1 Scopus citations

Abstract

In this paper, we perform the transient theoretical analysis of diffusion recursive least squares via signed error (DRLS-SE) algorithm over networks in the presence of impulsive noise. The obtained analytical models allow us to investigate the impacts of nonstationary system and cyclostationary colored inputs on the network transient convergence behavior. Simulations are provided to highlight the robustness of DRLS-SE algorithm against impulsive noise, and corroborate the correctness and accuracy of obtained theoretical findings.

Original languageEnglish
Title of host publication2022 IEEE 32nd International Workshop on Machine Learning for Signal Processing, MLSP 2022
PublisherIEEE Computer Society
ISBN (Electronic)9781665485470
DOIs
StatePublished - 2022
Event32nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2022 - Virtual, Online, China
Duration: 22 Aug 202225 Aug 2022

Publication series

NameIEEE International Workshop on Machine Learning for Signal Processing, MLSP
Volume2022-August
ISSN (Print)2161-0363
ISSN (Electronic)2161-0371

Conference

Conference32nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2022
Country/TerritoryChina
CityVirtual, Online
Period22/08/2225/08/22

Keywords

  • Diffusion RLS
  • cyclostationary colored inputs
  • impulsive noise
  • signed error
  • transient theoretical analysis

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