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@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"
}


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