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Fouille de données et segmentation de chroniques par extrema: considérations préliminaires

Abstract : Time series segmentation is one of the many data mining tools. We take here local extrema as perceptually interesting points (PIPs). The blurring of those PIPs by the quick fluctuations around any time series is treated via an additive decomposition theorem, due to Cartier and Perrin, and algebraic estimation techniques, which are already useful in automatic control and signal processing. Our approach is validated by several computer illustrations. They underline the importance of the choice of a threshold for the extrema detection.
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Contributor : Michel Fliess <>
Submitted on : Thursday, September 3, 2020 - 10:41:31 PM
Last modification on : Tuesday, September 22, 2020 - 3:33:54 PM

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  • HAL Id : hal-02929875, version 1
  • ARXIV : 2009.09895

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Michel Fliess, Cédric Join. Fouille de données et segmentation de chroniques par extrema: considérations préliminaires. 13ème Conférence Internationale de Modélisation, Optimisation et Simulation, MOSIM 2020, Nov 2020, Agadir, Maroc. ⟨hal-02929875⟩

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