@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 = "11 maio 2024"
}