Comparison of wavelet transform and Fourier transform applied to analysis of non-stationary processes
Аннотация
This article contains a comparison of three data analysis methods’ informativity: wavelet transform, Fourier transform and short-time Fourier transform. This work contains an attempt to find the most sensitive method for the detection of quasiharmonic components in experimental data that have pronounced non-stationary behavior.
Results of high-frequency near-field sounding, IR-spectroscopy and NMR analysis of water, and also model harmonic signal were used as non-stationary processes for analysis.
Об авторах
A. Drozdov
Institute for Analytical Instrumentation Russian Academy of Science
Россия
Россия
I. Pomortsev
ITMO University
Россия
Россия
K. Tyutyukin
St. Petersburg State University, Physical faculty
Россия
Россия
Y. Baloshin
ITMO University
Россия
Россия
Список литературы
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6. G. Bachman, L. Narici and E. Beckenstein. Fourier and Wavelet Analysis. Springer-Verlag, Berlin (2000).
7. J.F. Muzy, E. Bacry, A. Arneodo. Wavelets and multifractal formalism for singular signals: Application to turbulence data. Phys. Rev. Lett., 67, P. 3515–3518 (1991).
8. G. Kaiser. A friendly guide to wavelet. Boston, Basel, Berlin: Birkhauser (1994).
9. S.G. Krantz. A panorama of harmonic analysis. The mathematical association of America, Washington, D.C. (1999).
Рецензия
Для цитирования:
, , , . Наносистемы: физика, химия, математика. 2014;5(3):363-373.
For citation:
Drozdov A., Pomortsev I., Tyutyukin K., Baloshin Y. Comparison of wavelet transform and Fourier transform applied to analysis of non-stationary processes. Nanosystems: Physics, Chemistry, Mathematics. 2014;5(3):363-373.
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