Acceleration of time series entropy algorithms

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F19%3A10242124" target="_blank" >RIV/61989100:27740/19:10242124 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007%2Fs11227-018-2657-2" target="_blank" >https://link.springer.com/article/10.1007%2Fs11227-018-2657-2</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11227-018-2657-2" target="_blank" >10.1007/s11227-018-2657-2</a>

Result language
angličtina
Original language name
Acceleration of time series entropy algorithms
Original language description
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.
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
<a href="/en/project/LM2015070" target="_blank" >LM2015070: IT4Innovations National Supercomputing Center</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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