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Clustering using Sum-of-Norms Regularization: With Application to Particle Filter Output Computation
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2011 (English)Report (Other academic)
Abstract [en]

We present a novel clustering method, formulated as a convex optimization problem. The method is based on over-parameterization and uses a sum-of-norms (SON) regularization to control the trade-off between the model fit and the number of clusters. Hence, the number of clusters can be automatically adapted to best describe the data, and need not to be specified a priori. We apply SON clustering to cluster the particles in a particle filter, an application where the number of clusters is often unknown and time varying, making SON clustering an attractive alternative.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2011. , 6 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2993
Keyword [en]
Clustering ; Particle filter ; Sum-of-norms
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-97754ISRN: LiTH-ISY-R-2993OAI: oai:DiVA.org:liu-97754DiVA: diva2:650713
Projects
CADICS
Funder
Swedish Research Council
Available from: 2013-09-23 Created: 2013-09-23 Last updated: 2014-09-01Bibliographically approved

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fulltext(675 kB)389 downloads
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Type fulltextMimetype application/pdf

Authority records BETA

Lindsten, FredrikOhlsson, HenrikLjung, Lennart

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
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Output format
  • html
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