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Slope Entropy: A New Time Series Complexity Estimator Based on Both Symbolic Patterns and Amplitude Information

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Slope Entropy: A New Time Series Complexity Estimator Based on Both Symbolic Patterns and Amplitude Information

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Cuesta Frau, D. (2019). Slope Entropy: A New Time Series Complexity Estimator Based on Both Symbolic Patterns and Amplitude Information. Entropy. 21(12):1-22. https://doi.org/10.3390/e21121167

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Título: Slope Entropy: A New Time Series Complexity Estimator Based on Both Symbolic Patterns and Amplitude Information
Autor: Cuesta Frau, David
Entidad UPV: Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Fecha difusión:
Resumen:
[EN] The development of new measures and algorithms to quantify the entropy or related concepts of a data series is a continuous effort that has brought many innovations in this regard in recent years. The ultimate goal ...[+]
Palabras clave: Permutation entropy , Sample entropy , Signal classification , Symbolic dynamics , Discriminating power
Derechos de uso: Reconocimiento (by)
Fuente:
Entropy. (issn: 1099-4300 )
DOI: 10.3390/e21121167
Editorial:
MDPI AG
Versión del editor: https://doi.org/10.3390/e21121167
Tipo: Artículo

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