Parsimonious Segmentation of Time Series' by Potts Models

Winkler, Gerhard and Kempe, A. and Liebscher, V. and Wittich, O. (2003): Parsimonious Segmentation of Time Series' by Potts Models. Collaborative Research Center 386, Discussion Paper 348

Abstract

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.

• Item Type: Paper (Research Paper)
• Collections: Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386; Special Research Fields > Special Research Field 386
• Subjects: 500 Science > 510 Mathematics
• Language: English