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LMC and SDL Complexity Measures: A Tool to Explore Time Series
Joint Authors
Piqueira, José Roberto Castilho
Mattos, Sérgio Henrique Vannucchi Leme de
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-01-02
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
This work is a generalization of the López-Ruiz, Mancini, and Calbet (LMC) and Shiner, Davison, and Landsberg (SDL) complexity measures, considering that the state of a system or process is represented by a continuous temporal series of a dynamical variable.
As the two complexity measures are based on the calculation of informational entropy, an equivalent information source is defined by using partitions of the dynamical variable range.
During the time intervals, the information associated with the measured dynamical variable is the seed to calculate instantaneous LMC and SDL measures.
To show how the methodology works generating indicators, two examples, one concerning meteorological data and the other concerning economic data, are presented and discussed.
American Psychological Association (APA)
Piqueira, José Roberto Castilho& Mattos, Sérgio Henrique Vannucchi Leme de. 2019. LMC and SDL Complexity Measures: A Tool to Explore Time Series. Complexity،Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1131178
Modern Language Association (MLA)
Piqueira, José Roberto Castilho& Mattos, Sérgio Henrique Vannucchi Leme de. LMC and SDL Complexity Measures: A Tool to Explore Time Series. Complexity No. 2019 (2019), pp.1-8.
https://search.emarefa.net/detail/BIM-1131178
American Medical Association (AMA)
Piqueira, José Roberto Castilho& Mattos, Sérgio Henrique Vannucchi Leme de. LMC and SDL Complexity Measures: A Tool to Explore Time Series. Complexity. 2019. Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1131178
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1131178