Highly scalable algorithm for computation of recurrence quantitative analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F19%3A10242321" target="_blank" >RIV/61989100:27740/19:10242321 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/s11227-018-2350-5" target="_blank" >https://doi.org/10.1007/s11227-018-2350-5</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11227-018-2350-5" target="_blank" >10.1007/s11227-018-2350-5</a>
Alternative languages
Result language
angličtina
Original language name
Highly scalable algorithm for computation of recurrence quantitative analysis
Original language description
Recurrence plot analysis is a well-established method to analyse time seriesin numerous areas of research. However, it has exponential computational and spa-tial complexity. As the main result of this paper, a technique for the computation ofrecurrence quantitative analysis (RQA) is outlined. This method significantly reducesspatial complexity of computation by computing RQA directly from the time series,optimizing memory accesses and reducing computational time. Additionally, parallelimplementation of this technique is tested on the Salomon cluster and is proved to beextremely fast and scalable. This means that recurrence quantitative analysis may beapplied to longer time series or in applications with the need of real-time analysis
Czech name
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Czech description
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Classification
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)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Supercomputing
ISSN
0920-8542
e-ISSN
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Volume of the periodical
75
Issue of the periodical within the volume
3
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
12
Pages from-to
1175-1186
UT code for WoS article
000463635700015
EID of the result in the Scopus database
2-s2.0-85044730270