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Segmentation of Signals Using Piecewise Constant Linear Regression Models
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
1994 (English)Report (Other academic)
Abstract [en]

The signal segmentation approach described herein assumes that the signal can be accurately modelled by a linear regression with piece-wise constant parameters. A simultaneous estimate of the change times is considered. The maximum likelihood and maximum a posteriori probability estimates are derived after marginalization of the linear regression parameters and the measurement noise variance, which are considered as nuisance parameters. A well-known problem is that the complexity of segmentation increases exponentially in the number of data. Therefore, two inequalities are derived enabling the exact estimate to be computed with quadratic complexity. A linear in time complexity recursive approximation is proposed as well, based on these inequalities. The method is evaluated on a speech signal previously analyzed in literature, showing that a comparable result is obtained directly without the usual tuning effort. It is also detailed how it successfully has been applied in a car for online segmentation of the driven path for supporting guidance systems.

Place, publisher, year, edition, pages
Linköping: Linköping University , 1994. , 29 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 1672
Keyword [en]
Segmentation, Signal, Linear regression models
Keyword [sv]
Elektronik Kretsar
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-55138ISRN: LITH-ISY-R-1672OAI: oai:DiVA.org:liu-55138DiVA: diva2:315707
Available from: 2010-04-29 Created: 2010-04-29 Last updated: 2014-10-09Bibliographically approved

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Gustafsson, Fredrik

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CiteExportLink to record
Permanent link

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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