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A Unified Approach to PCA, PLS, MLR and CCA
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9267-2191
n/a.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9091-4724
1997 (English)Report (Other academic)
Abstract [en]

This paper presents a novel algorithm for analysis of stochastic processes. The algorithm can be used to find the required solutions in the cases of principal component analysis (PCA), partial least squares (PLS), canonical correlation analysis (CCA) or multiple linear regression (MLR). The algorithm is iterative and sequential in its structure and uses on-line stochastic approximation to reach an equilibrium point. A quotient between two quadratic forms is used as an energy function and it is shown that the equilibrium points constitute solutions to the generalized eigenproblem.

Place, publisher, year, edition, pages
Linköping, Sweden: Linköping University, Department of Electrical Engineering , 1997. , 26 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 1992
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-53334ISBN: 99-2575-218-3 (print)OAI: oai:DiVA.org:liu-53334DiVA: diva2:288565
Available from: 2010-01-21 Created: 2010-01-20 Last updated: 2014-10-08

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Borga, MagnusKnutsson, Hans

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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
  • oxford
  • 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