@Article{MagriniDomiMacaKiss:2020:ExSlFa,
               author = "Magrini, Luciano Aparecido and Domingues, Margarete Oliveira and 
                         Macau, Elbert Einstein Nehrer and Kiss, Istv{\'a}n Z.",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Saint Louis University}",
                title = "Extraction of slow and fast dynamics of multiple time scale 
                         systems using wavelet techniques",
              journal = "Chaos",
                 year = "2020",
               volume = "30",
               number = "6",
                pages = "e063139",
                month = "June",
             abstract = "A methodology is presented based on wavelet techniques to 
                         approximate fast and slow dynamics present in time-series whose 
                         behavior is characterized by different local scales in time. These 
                         approximations are useful to understand the global dynamics of the 
                         original full systems, especially in experimental situations where 
                         all information is contained in a one-dimensional time-series. 
                         Wavelet analysis is a natural approach to handle these 
                         approximations because each dynamical behavior manifests its 
                         specific subset in frequency domain, for example, with two time 
                         scales, the slow and fast dynamics, present in low and high 
                         frequencies, respectively. The proposed procedure is illustrated 
                         by the analysis of a complex experimental time-series of iron 
                         electrodissolution where the slow chaotic dynamics is interrupted 
                         by fast irregular spiking. The method can be used to first filter 
                         the time-series data and then separate the fast and slow dynamics 
                         even when clear maxima and/or minima in the corresponding global 
                         wavelet spectrum are missing. The results could find applications 
                         in the analysis of synchronization of complex systems through 
                         multi-scale analysis.",
                  doi = "10.1063/5.0004719",
                  url = "http://dx.doi.org/10.1063/5.0004719",
                 issn = "1054-1500",
             language = "en",
           targetfile = "magrini_extraction.pdf",
        urlaccessdate = "28 abr. 2024"
}