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Acceleration of time series entropy algorithms

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Abstract

This paper concentrates on the entropy estimation of time series. Two new algorithms are introduced: Fast Approximate Entropy and Fast Sample Entropy. Their main advantage is their lower time complexity. Examples considered in the paper include interesting experiments with real-world data obtained from IT4Innovations’ supercomputers Salomon and Anselm, as well as with data artificially created specifically to test the credibility of these new entropy analyzers.

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Acknowledgements

This work has been supported by the Large Infrastructures for Research, Experimental Development and Innovations project “IT4Innovations National Supercomputing Center LM2015070.”

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Authors and Affiliations

  1. IT4Innovations, VŠB - Technical University of Ostrava, 17.listopadu 15/2172, 708 33, Ostrava, Poruba, Czech Republic

    Jiří Tomčala

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  1. Jiří Tomčala
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Correspondence to Jiří Tomčala.

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Tomčala, J. Acceleration of time series entropy algorithms. J Supercomput 75, 1443–1454 (2019). https://doi.org/10.1007/s11227-018-2657-2

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  • DOI: https://doi.org/10.1007/s11227-018-2657-2

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