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Teoreticheskaya i Matematicheskaya Fizika, 2005, Volume 142, Number 1, Pages 148–159
DOI: https://doi.org/10.4213/tmf1771 (Mi tmf1771) 		 
This article is cited in 9 scientific papers (total in 9 papers)

The problem of processing time series: Extending possibilities of the local approximation method using singular spectrum analysis

I. A. Istomin, O. L. Kotlyarov, A. Yu. Loskutov

M. V. Lomonosov Moscow State University
Full-text PDF (325 kB) Citations (9)
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DOI: https://doi.org/10.4213/tmf1771
Abstract: We present algorithms for singular spectrum analysis and local approximation methods used to extrapolate time series. We analyze the advantages and disadvantages of these methods and consider the peculiarities of applying them to various systems. Based on this analysis, we propose a generalization of the local approximation method that makes it suitable for forecasting very noisy time series. We present the results of numerical simulations illustrating the possibilities of the proposed method.
Keywords: time series, forecast, chaos, local approximation.
Received: 11.11.2003
Revised: 03.06.2004
English version:
Theoretical and Mathematical Physics, 2005, Volume 142, Issue 1, Pages 128–137
DOI: https://doi.org/10.1007/s11232-005-0077-y
Bibliographic databases:
Language: Russian
Citation: I. A. Istomin, O. L. Kotlyarov, A. Yu. Loskutov, “The problem of processing time series: Extending possibilities of the local approximation method using singular spectrum analysis”, TMF, 142:1 (2005), 148–159; Theoret. and Math. Phys., 142:1 (2005), 128–137
Citation in format AMSBIB
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\jour Theoret. and Math. Phys.
\yr 2005
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Linking options:
  • https://www.mathnet.ru/eng/tmf1771
  • https://doi.org/10.4213/tmf1771
  • https://www.mathnet.ru/eng/tmf/v142/i1/p148
    • This publication is cited in the following 9 articles:
    1. Alexandr Volvach, Galina Kurbasova, Larisa Volvach, “Wavelets in the analysis of local time series of the Earth's surface air”, Heliyon, 10:1 (2024), e23237  crossref
    2. V. N. Efanov, N. S. Ivanova, “Expert System for Assessing the Technical Status of Gas Turbine Engines Using the Knowledge Base of Temporal Precedents”, Russ. Aeronaut., 66:1 (2023), 64  crossref
    3. V. N. Efanov, N. S. Ivanova, 2023 International Ural Conference on Electrical Power Engineering (UralCon), 2023, 628  crossref
    4. D. A. Anikeev, G. O. Penkin, V. V. Strizhov, “Klassifikatsiya fizicheskoi aktivnosti cheloveka s pomoschyu lokalnykh approksimiruyuschikh modelei”, Inform. i ee primen., 13:1 (2019), 40–48  mathnet  crossref  elib
    5. Krutikov V.N., Indenko O.N., Chernova E.S., 2018 International Scientific Multi-Conference on Industrial Engineering and Modern Technologies (Fareastcon), IEEE, 2018  isi
    6. Vladimir N. Krutikov, Oksana N. Indenko, Ekaterina S. Chernova, 2018 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon), 2018, 1  crossref
    7. Xie H.-B., Guo T., Sivakumar B., Liew A.W.-Ch., Dokos S., “Symplectic Geometry Spectrum Analysis of Nonlinear Time Series”, Proc. R. Soc. A-Math. Phys. Eng. Sci., 470:2170 (2014), 20140409  crossref  mathscinet  isi  scopus  scopus
    8. Mirmomeni M., Lucas C., Araabi B.N., Moshiri B., Bidar M.R., “Recursive spectral analysis of natural time series based on eigenvector matrix perturbation for online applications”, Iet Signal Processing, 5:6 (2011), 515–526  crossref  mathscinet  isi  scopus  scopus
    9. A. Yu. Loskutov, “Fascination of chaos”, Phys. Usp., 53:12 (2010), 1257–1280  mathnet  crossref  crossref  adsnasa  isi  elib
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    		Теоретическая и математическая физика Theoretical and Mathematical Physics
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