Quantile graphs for the characterization of chaotic dynamics in time series

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorDe Oliveira Campanharo, Andriana Susana Lopes-
Autor(es): dc.creatorRamos, Fernando Manuel-
Data de aceite: dc.date.accessioned2025-08-21T15:12:31Z-
Data de disponibilização: dc.date.available2025-08-21T15:12:31Z-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2016-06-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/ICoCS.2015.7483302-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/228184-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/228184-
Descrição: dc.descriptionRecently, a map from time series to networks with an approximate inverse operation has been proposed [1], allowing the use network statistics to characterize time series and time series statistics to characterize networks. In this approach, time series quantiles are mapped into nodes of a graph [1], [2]. Here we show these quantile graphs (QGs) are able to characterize features such as long range correlations or deterministic chaos present in the underlying dynamics of the original signal, making them a powerful tool for the analysis of nonlinear systems. As an illustration we applied the QG method to the Logistic and the Quadratic maps, for varying values of their control parameters. We show that in both cases the main features of resulting bifurcation cascades, with their progressive transition from periodic behavior to chaos, are well captured by the topology of QGs.-
Descrição: dc.descriptionDepartamento de Bioestatística Instituto de Biociências Universidade Estadual Paulista-
Descrição: dc.descriptionDepartamento de Bioestatística Instituto de Biociências Universidade Estadual Paulista-
Idioma: dc.languageen-
Relação: dc.relationProceedings of 2015 IEEE World Conference on Complex Systems, WCCS 2015-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectChaotic System-
Palavras-chave: dc.subjectComplex Networks-
Palavras-chave: dc.subjectNonlinear Time Series-
Palavras-chave: dc.subjectQuantile Graphs-
Título: dc.titleQuantile graphs for the characterization of chaotic dynamics in time series-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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