Quantifying sudden changes in dynamical systems using symbolic networks

Autor:	Masoller, Cristina, Hong, Yanhua, Ayad, Sarah, Gustave, Francois, Barland, Stephane, Pons, Antonio J., Gómez, Sergio, Arenas, Alex
Rok vydání:	2015
Předmět:	Physics - Physics and Society Nonlinear Sciences - Chaotic Dynamics Physics - Data Analysis Statistics and Probability Physics - Optics
Zdroj:	New Journal of Physics 17 (2015) 023068
Druh dokumentu:	Working Paper
DOI:	10.1088/1367-2630/17/2/023068
Popis:	We characterise the evolution of a dynamical system by combining two well-known complex systems' tools, namely, symbolic ordinal analysis and networks. From the ordinal representation of a time-series we construct a network in which every node weights represents the probability of an ordinal patterns (OPs) to appear in the symbolic sequence and each edges weight represents the probability of transitions between two consecutive OPs. Several network-based diagnostics are then proposed to characterize the dynamics of different systems: logistic, tent and circle maps. We show that these diagnostics are able to capture changes produced in the dynamics as a control parameter is varied. We also apply our new measures to empirical data from semiconductor lasers and show that they are able to anticipate the polarization switchings, thus providing early warning signals of abrupt transitions. Comment: 18 pages, 9 figures, to appear in New Journal of Physics
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1501.06790 Zobrazit plný text záznamu View this record from Arxiv