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Performance Analysis of General Tracking Algorithms
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
1994 (English)Report (Other academic)
Abstract [en]

A general family of tracking algorithms for linear regression models is studied. It includes the familiar LMS (gradient approach), RLS (recursive least squares) and KF (Kalman filter) based estimators. The exact expressions for the quality of the obtained estimates are complicated. Approximate, and easy-to-use, expressions for the covariance matrix of the parameter tracking error are developed. These are applicable over whole time interval, including the transient and the approximation error can be explicitly calculated.

Place, publisher, year, edition, pages
Linköping: Linköping University , 1994. , 16 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 1664
Keyword [en]
Linear regression models, Kalman filters, Covariance matrices
Keyword [sv]
Cybernetik Informationsteori, Maskinelement Servomekanismer Automation
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-55130ISRN: LITH-ISY-R-1664OAI: oai:DiVA.org:liu-55130DiVA: diva2:315717
Available from: 2010-04-29 Created: 2010-04-29 Last updated: 2014-09-18Bibliographically approved

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Ljung, Lennart

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • asciidoc
  • rtf