Arbeitspapier

Parsimonious segmentation of time series' by Potts models

Typical problems in the analysis of data sets like time-series or images crucially rely on the extraction of primitive features based on segmentation. Variational approaches are a popular and convenient framework in which such problems can be studied. We focus on Potts models as simple nontrivial instances. The discussion proceeds along two data sets from brain mapping and functional genomics.

Language
Englisch

Bibliographic citation
Series: Discussion Paper ; No. 348

Event
Geistige Schöpfung
(who)
Winkler, Gerhard
Kempe, Angela
Liebscher, Volkmar
Wittich, Olaf
Event
Veröffentlichung
(who)
Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen
(where)
München
(when)
2003

DOI
doi:10.5282/ubm/epub.1724
Handle
URN
urn:nbn:de:bvb:19-epub-1724-6
Last update
10.03.2025, 11:41 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Winkler, Gerhard
  • Kempe, Angela
  • Liebscher, Volkmar
  • Wittich, Olaf
  • Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen

Time of origin

  • 2003

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