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| Campo DC | Valor | Lengua/Idioma |
|---|---|---|
| dc.creator | Gonçalves, Bruna Amin | - |
| dc.creator | Carpi, Laura | - |
| dc.creator | Rosso, Osvaldo Aníbal | - |
| dc.creator | Ravetti, Martín G. | - |
| dc.date | 2018-05-29T21:37:21Z | - |
| dc.date | 2018-05-29T21:37:21Z | - |
| dc.date | 2016-12 | - |
| dc.date | 2018-05-29T18:36:49Z | - |
| dc.date.accessioned | 2019-04-29T15:54:06Z | - |
| dc.date.available | 2019-04-29T15:54:06Z | - |
| dc.date.issued | 2016-12 | - |
| dc.identifier | Gonçalves, Bruna Amin; Carpi, Laura; Rosso, Osvaldo Aníbal; Ravetti, Martín G.; Time series characterization via horizontal visibility graph and Information Theory; Elsevier Science; Physica A: Statistical Mechanics and its Applications; 464; 12-2016; 93-102 | - |
| dc.identifier | 0378-4371 | - |
| dc.identifier | http://hdl.handle.net/11336/46546 | - |
| dc.identifier | CONICET Digital | - |
| dc.identifier | CONICET | - |
| dc.identifier.uri | http://rodna.bn.gov.ar:8080/jspui/handle/bnmm/305024 | - |
| dc.description | Complex networks theory have gained wider applicability since methods for transformation of time series to networks were proposed and successfully tested. In the last few years, horizontal visibility graph has become a popular method due to its simplicity and good results when applied to natural and artificially generated data. In this work, we explore different ways of extracting information from the network constructed from the horizontal visibility graph and evaluated by Information Theory quantifiers. Most works use the degreedistribution of the network, however, we found alternative probability distributions, more efficient than the degree distribution in characterizing dynamical systems. In particular, we find that, when using distributions based on distances and amplitude values, significant shorter time series are required. We analyze fractional Brownian motion time series, and a paleoclimatic proxy record of ENSO from the Pallcacocha Lake to study dynamical changes during the Holocene. | - |
| dc.description | Fil: Gonçalves, Bruna Amin. Universidade Federal de Minas Gerais; Brasil | - |
| dc.description | Fil: Carpi, Laura. Universidad Politécnica de Catalunya; España | - |
| dc.description | Fil: Rosso, Osvaldo Aníbal. Universidade Federal de Alagoas; Brasil. Instituto Tecnológico de Buenos Aires; Argentina. Universidad de los Andes; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina | - |
| dc.description | Fil: Ravetti, Martín G.. Universidade Federal de Minas Gerais; Brasil | - |
| dc.format | application/pdf | - |
| dc.format | application/pdf | - |
| dc.language | eng | - |
| dc.publisher | Elsevier Science | - |
| dc.relation | info:eu-repo/semantics/altIdentifier/doi/https://dx.doi.org/10.1016/j.physa.2016.07.063 | - |
| dc.relation | info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0378437116304940 | - |
| dc.rights | info:eu-repo/semantics/restrictedAccess | - |
| dc.rights | https://creativecommons.org/licenses/by-nc-nd/2.5/ar/ | - |
| dc.source | reponame:CONICET Digital (CONICET) | - |
| dc.source | instname:Consejo Nacional de Investigaciones Científicas y Técnicas | - |
| dc.source | instacron:CONICET | - |
| dc.subject | TIME SERIES ANALYSIS | - |
| dc.subject | COMPLEX NETWORKS | - |
| dc.subject | INFORMATION THEORY QUANTIFIERS | - |
| dc.subject | Astronomía | - |
| dc.subject | Ciencias Físicas | - |
| dc.subject | CIENCIAS NATURALES Y EXACTAS | - |
| dc.title | Time series characterization via horizontal visibility graph and Information Theory | - |
| dc.type | info:eu-repo/semantics/article | - |
| dc.type | info:eu-repo/semantics/publishedVersion | - |
| dc.type | info:ar-repo/semantics/articulo | - |
| Aparece en las colecciones: | CONICET | |
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