A filtering based recursive least squares estimation algorithm for pseudo-linear auto-regressive systems

Sheng Ding, Rui Ding, Erfu Yang

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

This paper uses the filtering technique, transforms a pseudo-linear auto-regressive system into an identification model and presents a new recursive least squares parameter estimation algorithm pseudo-linear auto-regressive systems. The proposed algorithm has a high computational efficiency because the dimensions of its covariance matrices become small compared with the recursive generalized least squares algorithm.

Original languageEnglish
Pages (from-to)1801-1809
Number of pages9
JournalJournal of the Franklin Institute
Volume351
Issue number3
Early online date22 Nov 2013
DOIs
Publication statusPublished - Mar 2014

Keywords

  • filtering
  • identification model
  • least squares parameter estimation
  • signal processing

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