@Article{MagriniDomiMend:2017:CaStBa,
               author = "Magrini, Luciano Aparecido and Domingues, Margarete Oliveira and 
                         Mendes J{\'u}nior, Odim",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "On the Effects of Gaps and Uses of Approximation Functions on the 
                         Time-Scale Signal Analysis: A Case Study Based on Space 
                         Geophysical Events",
              journal = "Brazilian Journal of Physics",
                 year = "2017",
               volume = "47",
               number = "2",
                pages = "167--181",
                month = "Apr.",
             keywords = "Adaptive wavelet, Data treatment, Numeric approximations, Signals 
                         with gaps, Space Geophysics.",
             abstract = "The presence of gaps is quite common in signals related to space 
                         science phenomena. Usually, this presence prevents the direct use 
                         of standard time-scale analysis because this analysis needs 
                         equally spaced data; it is affected by the time series borders 
                         (boundaries), and gaps can cause an increase of internal borders. 
                         Numerical approximations can be used to estimate the records whose 
                         entries are gaps. However, their use has limitations. In many 
                         practical cases, these approximations cannot faithfully reproduce 
                         the original signal behaviour. Alternatively, in this work, we 
                         compare an adapted wavelet technique (gaped wavelet transform), 
                         based on the continuous wavelet transform with Morlet wavelet 
                         analysing function, with two other standard approximation methods, 
                         namely, spline and Hermite cubic polynomials. This wavelet method 
                         does not require an approximation of the data on the gap 
                         positions, but it adapts the analysing wavelet function to deal 
                         with the gaps. To perform our comparisons, we use 120 magnetic 
                         field time series from a well-known space geophysical phenomena 
                         and we select and classify their gaps. Then, we analyse the 
                         influence of these methods in two time-scale tools. As 
                         conclusions, we observe that when the gaps are small (very few 
                         points sequentially missing), all the methods work well. However, 
                         with large gaps, the adapted wavelet method presents a better 
                         performance in the time-scale representation. Nevertheless, the 
                         cubic Hermite polynomial approximation is also an option when a 
                         reconstruction of the data is also needed, with the price of 
                         having a worse time-scale representation than the adapted wavelet 
                         method.",
                  doi = "10.1007/s13538-017-0486-z",
                  url = "http://dx.doi.org/10.1007/s13538-017-0486-z",
                 issn = "0103-9733",
             language = "en",
           targetfile = "magrini_effects.pdf",
        urlaccessdate = "28 abr. 2024"
}