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Zhurnal Vychislitel'noi Matematiki i Matematicheskoi Fiziki, 2021, Volume 61, Number 7, Pages 1113–1124
DOI: https://doi.org/10.31857/S0044466921070048 (Mi zvmmf11262) 		 
This article is cited in 5 scientific papers (total in 5 papers)

Computer science

Morphological and other research techniques for almost cyclic time series as applied to CO$_2$ concentration series

V. K. Avilova, V. S. Aleshnovskiib, A. V. Bezrukovab, V. A. Gazaryanbc, N. A. Zyuzinab, Yu. A. Kurbatovaa, D. A. Tarbaevb, A. I. Chulichkovdb, N. E. Shapkinabe

a Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, 119071, Moscow, Russia
b Faculty of Physics, Lomonosov Moscow State University, 119991, Moscow, Russia
c Financial University under the Government of the Russian Federation, 125993, Moscow, Russia
d Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, 119017, Moscow, Russia
e Institute for Theoretical and Applied Electromagnetics, Russian Academy of Sciences, 125412, Moscow, Russia
Citations (5)
DOI: https://doi.org/10.31857/S0044466921070048
Abstract: Based on the morphological analysis techniques developed under the guidance of Yu. P. Pyt'ev, a method for filtering time series is proposed that is capable of detecting an almost cyclic component with a varying cycle length and varying series members within cycles. The effectiveness of the approach is illustrated as applied to decomposition of time series of atmospheric СО$_2$ concentrations. After filtering out the series component responsible for diurnal variability, the series residual becomes stationary, so mathematical statistical methods and Fourier analysis can be used for its further investigation. The results are verified by comparing them with Fourier analysis data. A cyclicity with a period longer than one day is studied using Fourier expansion and wavelet analysis of the original series.
Key words: digital signal processing, quasi-periodic signals, decomposition, waveform, Fourier analysis, wavelet analysis.
Funding agency Grant number
Russian Foundation for Basic Research 19-29-09044
This work was supported in part by the Russian Foundation for Basic Research, project no. 19-29-09044.
Received: 26.11.2020
Revised: 26.11.2020
Accepted: 11.03.2021
English version:
Computational Mathematics and Mathematical Physics, 2021, Volume 61, Issue 7, Pages 1106–1117
DOI: https://doi.org/10.1134/S0965542521070046
Bibliographic databases:
Document Type: Article
UDC: 519.72
Language: Russian
Citation: V. K. Avilov, V. S. Aleshnovskii, A. V. Bezrukova, V. A. Gazaryan, N. A. Zyuzina, Yu. A. Kurbatova, D. A. Tarbaev, A. I. Chulichkov, N. E. Shapkina, “Morphological and other research techniques for almost cyclic time series as applied to CO$_2$ concentration series”, Zh. Vychisl. Mat. Mat. Fiz., 61:7 (2021), 1113–1124; Comput. Math. Math. Phys., 61:7 (2021), 1106–1117
Citation in format AMSBIB
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\jour Zh. Vychisl. Mat. Mat. Fiz.
\yr 2021
\vol 61
\issue 7
\pages 1113--1124
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\crossref{https://doi.org/10.31857/S0044466921070048}
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    • This publication is cited in the following 5 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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