Detecting dynamical changes in time series by using the Jensen Shannon divergence

Fil: Mateos, Diego Martín. University of Toronto. Hospital for Sick Children; Canadá.

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Detalles Bibliográficos
Autores principales: Mateos, Diego Martín, Riveaud, Leonardo Esteban, Lamberti, Pedro Walter
Otros Autores: https://orcid.org/0000-0002-1953-0875
Formato: publishedVersion article
Lenguaje:Inglés
Publicado: 2024
Materias:
Chaos
Noise
Jensen Shannon divergence
Acceso en línea:http://hdl.handle.net/11086/553789
https://dx.doi.org/10.1063/1.4999613
Aporte de:
Repositorio Digital Universitario (UNC) de Universidad Nacional de Córdoba
id I10-R141-11086-553789
record_format dspace
spelling I10-R141-11086-5537892024-09-25T16:05:24Z Detecting dynamical changes in time series by using the Jensen Shannon divergence Mateos, Diego Martín Riveaud, Leonardo Esteban Lamberti, Pedro Walter https://orcid.org/0000-0002-1953-0875 Chaos Noise Jensen Shannon divergence info:eu-repo/semantics/publishedVersion Fil: Mateos, Diego Martín. University of Toronto. Hospital for Sick Children; Canadá. Fil: Riveaud, Leonardo Esteban. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Riveaud, Leonardo Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fil: Lamberti, Pedro Walter. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Lamberti, Pedro Walter. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Most of the time series in nature are a mixture of signals with deterministic and random dynamics. Thus the distinction between these two characteristics becomes important. Distinguishing between chaotic and aleatory signals is difficult because they have a common wide band power spectrum, a delta like autocorrelation function, and share other features as well. In general, signals are presented as continuous records and require to be discretized for being analyzed. In this work, we introduce different schemes for discretizing and for detecting dynamical changes in time series. One of the main motivations is to detect transitions between the chaotic and random regime. The tools here used here originate from the Information Theory. The schemes proposed are applied to simulated and real life signals, showing in all cases a high proficiency for detecting changes in the dynamics of the associated time series. http://aip.scitation.org/doi/10.1063/1.4999613 info:eu-repo/semantics/publishedVersion Fil: Mateos, Diego Martín. University of Toronto. Hospital for Sick Children; Canadá. Fil: Riveaud, Leonardo Esteban. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Riveaud, Leonardo Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fil: Lamberti, Pedro Walter. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Lamberti, Pedro Walter. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Otras Ciencias Físicas 2024-09-25T14:15:12Z 2024-09-25T14:15:12Z 2017 article Mateos, D. M., Riveaud, L. E. y Lamberti, P. W. (2017). Detecting dynamical changes in time series by using the Jensen Shannon divergence. Chaos: An Interdisciplinary Journal of Nonlinear Science, 27 (8), 083118. https://dx.doi.org/10.1063/1.4999613 1054-1500 http://hdl.handle.net/11086/553789 1089-7682 https://dx.doi.org/10.1063/1.4999613 eng Atribución-NoComercial-SinDerivadas 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/deed.es Impreso; Electrónico y/o Digital
institution Universidad Nacional de Córdoba
institution_str I-10
repository_str R-141
collection Repositorio Digital Universitario (UNC)
language Inglés
topic Chaos
Noise
Jensen Shannon divergence
spellingShingle Chaos
Noise
Jensen Shannon divergence
Mateos, Diego Martín
Riveaud, Leonardo Esteban
Lamberti, Pedro Walter
Detecting dynamical changes in time series by using the Jensen Shannon divergence
topic_facet Chaos
Noise
Jensen Shannon divergence
description Fil: Mateos, Diego Martín. University of Toronto. Hospital for Sick Children; Canadá.
author2 https://orcid.org/0000-0002-1953-0875
author_facet https://orcid.org/0000-0002-1953-0875
Mateos, Diego Martín
Riveaud, Leonardo Esteban
Lamberti, Pedro Walter
format publishedVersion
article
author Mateos, Diego Martín
Riveaud, Leonardo Esteban
Lamberti, Pedro Walter
author_sort Mateos, Diego Martín
title Detecting dynamical changes in time series by using the Jensen Shannon divergence
title_short Detecting dynamical changes in time series by using the Jensen Shannon divergence
title_full Detecting dynamical changes in time series by using the Jensen Shannon divergence
title_fullStr Detecting dynamical changes in time series by using the Jensen Shannon divergence
title_full_unstemmed Detecting dynamical changes in time series by using the Jensen Shannon divergence
title_sort detecting dynamical changes in time series by using the jensen shannon divergence
publishDate 2024
url http://hdl.handle.net/11086/553789
https://dx.doi.org/10.1063/1.4999613
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