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• W2000259494 endingPage "e108004" @default.
• W2000259494 startingPage "e108004" @default.
• W2000259494 abstract "A recently proposed methodology called the Horizontal Visibility Graph (HVG) [Luque et al., Phys. Rev. E., 80, 046103 (2009)] that constitutes a geometrical simplification of the well known Visibility Graph algorithm [Lacasa et al., Proc. Natl. Sci. U.S.A. 105, 4972 (2008)], has been used to study the distinction between deterministic and stochastic components in time series [L. Lacasa and R. Toral, Phys. Rev. E., 82, 036120 (2010)]. Specifically, the authors propose that the node degree distribution of these processes follows an exponential functional of the form , in which is the node degree and is a positive parameter able to distinguish between deterministic (chaotic) and stochastic (uncorrelated and correlated) dynamics. In this work, we investigate the characteristics of the node degree distributions constructed by using HVG, for time series corresponding to chaotic maps, 2 chaotic flows and different stochastic processes. We thoroughly study the methodology proposed by Lacasa and Toral finding several cases for which their hypothesis is not valid. We propose a methodology that uses the HVG together with Information Theory quantifiers. An extensive and careful analysis of the node degree distributions obtained by applying HVG allow us to conclude that the Fisher-Shannon information plane is a remarkable tool able to graphically represent the different nature, deterministic or stochastic, of the systems under study." @default.
• W2000259494 created "2016-06-24" @default.
• W2000259494 creator A5003258695 @default.
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• W2000259494 creator A5055912992 @default.
• W2000259494 date "2014-09-23" @default.
• W2000259494 modified "2023-10-18" @default.
• W2000259494 title "Distinguishing Noise from Chaos: Objective versus Subjective Criteria Using Horizontal Visibility Graph" @default.
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• W2000259494 doi "https://doi.org/10.1371/journal.pone.0108004" @default.
• W2000259494 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4172653" @default.
• W2000259494 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/25247303" @default.
• W2000259494 hasPublicationYear "2014" @default.
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