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Synchronization of networks of chaotic oscillators: Structural and dynamical datasets

We provide the topological structure of a series of N=28 Rössler chaotic oscillators diffusively coupled through one of its variables. The dynamics of the y variable describing the evolution of the individual nodes of the network are given for a wide range of coupling strengths. Datasets capture the...

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Detalles Bibliográficos
Autores principales: Sevilla-Escoboza, Ricardo, Buldú, Javier M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5063795/
https://www.ncbi.nlm.nih.gov/pubmed/27761501
http://dx.doi.org/10.1016/j.dib.2016.03.097
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author Sevilla-Escoboza, Ricardo
Buldú, Javier M.
author_facet Sevilla-Escoboza, Ricardo
Buldú, Javier M.
author_sort Sevilla-Escoboza, Ricardo
collection PubMed
description We provide the topological structure of a series of N=28 Rössler chaotic oscillators diffusively coupled through one of its variables. The dynamics of the y variable describing the evolution of the individual nodes of the network are given for a wide range of coupling strengths. Datasets capture the transition from the unsynchronized behavior to the synchronized one, as a function of the coupling strength between oscillators. The fact that both the underlying topology of the system and the dynamics of the nodes are given together makes this dataset a suitable candidate to evaluate the interplay between functional and structural networks and serve as a benchmark to quantify the ability of a given algorithm to extract the structural network of connections from the observation of the dynamics of the nodes. At the same time, it is possible to use the dataset to analyze the different dynamical properties (randomness, complexity, reproducibility, etc.) of an ensemble of oscillators as a function of the coupling strength.
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spelling pubmed-50637952016-10-19 Synchronization of networks of chaotic oscillators: Structural and dynamical datasets Sevilla-Escoboza, Ricardo Buldú, Javier M. Data Brief Data Article We provide the topological structure of a series of N=28 Rössler chaotic oscillators diffusively coupled through one of its variables. The dynamics of the y variable describing the evolution of the individual nodes of the network are given for a wide range of coupling strengths. Datasets capture the transition from the unsynchronized behavior to the synchronized one, as a function of the coupling strength between oscillators. The fact that both the underlying topology of the system and the dynamics of the nodes are given together makes this dataset a suitable candidate to evaluate the interplay between functional and structural networks and serve as a benchmark to quantify the ability of a given algorithm to extract the structural network of connections from the observation of the dynamics of the nodes. At the same time, it is possible to use the dataset to analyze the different dynamical properties (randomness, complexity, reproducibility, etc.) of an ensemble of oscillators as a function of the coupling strength. Elsevier 2016-04-04 /pmc/articles/PMC5063795/ /pubmed/27761501 http://dx.doi.org/10.1016/j.dib.2016.03.097 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Sevilla-Escoboza, Ricardo
Buldú, Javier M.
Synchronization of networks of chaotic oscillators: Structural and dynamical datasets
title Synchronization of networks of chaotic oscillators: Structural and dynamical datasets
title_full Synchronization of networks of chaotic oscillators: Structural and dynamical datasets
title_fullStr Synchronization of networks of chaotic oscillators: Structural and dynamical datasets
title_full_unstemmed Synchronization of networks of chaotic oscillators: Structural and dynamical datasets
title_short Synchronization of networks of chaotic oscillators: Structural and dynamical datasets
title_sort synchronization of networks of chaotic oscillators: structural and dynamical datasets
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5063795/
https://www.ncbi.nlm.nih.gov/pubmed/27761501
http://dx.doi.org/10.1016/j.dib.2016.03.097
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