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Investigation of Details in the Transition to Synchronization in Complex Networks by Using Recurrence Analysis

Departamento de Física, Universidade Federal do Paraná, 81531-980 Curitiba, PR, Brazil
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Math. Comput. Appl. 2019, 24(2), 42; https://doi.org/10.3390/mca24020042
Received: 18 March 2019 / Revised: 10 April 2019 / Accepted: 17 April 2019 / Published: 20 April 2019
(This article belongs to the Special Issue Dynamics Days Latin America and the Caribbean 2018)
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Abstract

The study of synchronization in complex networks is useful for understanding a variety of systems, including neural systems. However, the properties of the transition to synchronization are still not well known. In this work, we analyze the details of the transition to synchronization in complex networks composed of bursting oscillators under small-world and scale-free topologies using recurrence quantification analysis, specifically the determinism. We demonstrate the existence of non-stationarity states in the transition region. In the small-world network, the transition region denounces the existence of two-state intermittency. View Full-Text
Keywords: neural network; synchronization; nonlinear dynamics neural network; synchronization; nonlinear dynamics
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Budzinski, R.C.; Boaretto, B.R.R.; Prado, T.L.; Lopes, S.R. Investigation of Details in the Transition to Synchronization in Complex Networks by Using Recurrence Analysis. Math. Comput. Appl. 2019, 24, 42.

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