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Least squares identification algorithm based on two-step update estimation for wiener system

  • Rui Qi Dong
  • , Yi Yang Zhang*
  • , Ying-Zhang
  • , Hao Wei Guan
  • *Corresponding author for this work

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

Abstract

In this paper, a least squares based on two-step update identification algorithm is established for the Wiener system by introducing a relaxation factor, which controls the relative importance of the two estimation parts. In addition, the convergence performance of the proposed LS-TSU algorithm is then analyzed. It is shown by a numerical example that if the weighting factor is appropriately chosen, the proposed LS-TSU algorithm can possess faster convergence speed and higher convergence precision compared with the standard LS algorithm.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Information and Automation, ICIA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1039-1043
Number of pages5
ISBN (Electronic)9781538631546
DOIs
StatePublished - 20 Oct 2017
Externally publishedYes
Event2017 IEEE International Conference on Information and Automation, ICIA 2017 - Macau, China
Duration: 18 Jul 201720 Jul 2017

Publication series

Name2017 IEEE International Conference on Information and Automation, ICIA 2017

Conference

Conference2017 IEEE International Conference on Information and Automation, ICIA 2017
Country/TerritoryChina
CityMacau
Period18/07/1720/07/17

Keywords

  • Least squares
  • System identification
  • Update estimation
  • Wiener system

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