@Article{FreitasLaceMaca:2019:CoNeAp,
author = "Freitas, Vander Lu{\'{\i}}s de Souza and Lacerda, Juliana
Cestari and Macau, Elbert Einstein Nehrer",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)}",
title = "Complex networks approach for dynamical characterization of
nonlinear systems",
journal = "International Journal of Bifurcation and Chaos",
year = "2019",
volume = "29",
number = "13",
pages = "e1950188",
month = "Dec.",
keywords = "Nonlinear dynamics, complex networks, time series analysis.",
abstract = "Bifurcation diagrams and Lyapunov exponents are the main tools for
dynamical systems characterization. However, they are often
computationally expensive and complex to calculate. We present two
approaches for dynamical characterization of nonlinear systems via
the generation of an undirected complex network that is built from
their time series. Periodic windows and chaos can be detected by
analyzing network statistics like average degree, density and
betweenness centrality. Results are assessed in two discrete time
nonlinear maps.",
doi = "10.1142/S0218127419501888",
url = "http://dx.doi.org/10.1142/S0218127419501888",
issn = "0218-1274 and 1793-6551",
language = "en",
targetfile = "freitas_complex.pdf",
urlaccessdate = "28 mar. 2024"
}