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Mean-squared error experiment design for linear regression models
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. (System Identification Group)ORCID iD: 0000-0002-9368-3079
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. (System Identification Group)ORCID iD: 0000-0003-0355-2663
2012 (English)In: 16th IFAC Symposium on System Identification, IFAC , 2012, 1629-1634 p.Conference paper, Published paper (Refereed)
Abstract [en]

This work solves an experiment design problem for a linear regression problem using a reduced order model. The quality of the model is assessed using a mean square error measure that depends linearly on the parameters. The designed input signal ensures a predefined quality of the model while minimizing the input energy.

Place, publisher, year, edition, pages
IFAC , 2012. 1629-1634 p.
Series
IFAC Proceedings Volumes (IFAC-PapersOnline), ISSN 1474-6670 ; 16
Keyword [en]
Input and excitation design, Maximum likelihood methods
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-72584DOI: 10.3182/20120711-3-BE-2027.00339Scopus ID: 2-s2.0-84867071092ISBN: 978-390282306-9 (print)OAI: oai:DiVA.org:kth-72584DiVA: diva2:488377
Conference
Universite Libre de Bruxelles;Bruxelles; 11 July 2012 through 13 July 2012
Funder
ICT - The Next Generation
Note

QC 20121122

Available from: 2012-02-01 Created: 2012-01-31 Last updated: 2013-04-15Bibliographically approved

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Authority records BETA

Hjalmarsson, HåkanRojas, Cristian R.

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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
  • html
  • text
  • asciidoc
  • rtf