1d-SAX : une nouvelle représentation symbolique pour les séries temporelles

Abstract : SAX (Symbolic Aggregate approXimation) is one of the main symbolization techniques for time series. A well-known limitation of SAX is that trends are not taken into account in the symbolization. This paper proposes 1d-SAX a method to represent a time series as a sequence of symbols that each contain information about the average and the trend of the series on a segment. We compare the efficiency of SAX and 1d-SAX in a satellite image time series classification scheme. Results show that 1d-SAX improves performance using equal quantity of information.
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Conference papers
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https://hal.inria.fr/hal-00916970
Contributor : Thomas Guyet <>
Submitted on : Wednesday, December 11, 2013 - 9:41:51 AM
Last modification on : Wednesday, February 6, 2019 - 11:28:02 AM

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  • HAL Id : hal-00916970, version 1

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Simon Malinowski, Thomas Guyet, René Quiniou, Romain Tavenard. 1d-SAX : une nouvelle représentation symbolique pour les séries temporelles. Conférence Extraction et Gestion de Connaissances, Jan 2014, Rennes, France. ⟨hal-00916970⟩

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