Abstract
The purpose of this paper is to evidence why wavelet-based estimators are naturally matched to the spectrum analysis of 1/f processes. It is shown how the revisiting of classical spectral estimators from a time-frequency perspective allows to define different wavelet-based generalizations which are proved to be statistically and computationally efficient. Discretization issues (in time and scale) are discussed in some detail, theoretical claims are supported by numerical experiments and the importance of the proposed approach in turbulence studies is underlined.
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Abry, P., Gonçalvès, P., Flandrin, P. (1995). Wavelets, spectrum analysis and 1/f processes. In: Antoniadis, A., Oppenheim, G. (eds) Wavelets and Statistics. Lecture Notes in Statistics, vol 103. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2544-7_2
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DOI: https://doi.org/10.1007/978-1-4612-2544-7_2
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