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The Journal of Supercomputing

, Volume 75, Issue 3, pp 1443–1454 | Cite as

Acceleration of time series entropy algorithms

  • Jiří TomčalaEmail author
Article
  • 83 Downloads

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.

Keywords

Entropy Approximate entropy Sample entropy Fast Approximate Entropy Fast Sample Entropy 

Notes

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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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.IT4InnovationsVŠB - Technical University of OstravaOstrava, PorubaCzech Republic

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