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TMF, 2005, Volume 142, Number 1, Pages 148–159 (Mi tmf1771)  

This article is cited in 5 scientific papers (total in 5 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

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

DOI: https://doi.org/10.4213/tmf1771

Full text: PDF file (325 kB)
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English version:
Theoretical and Mathematical Physics, 2005, 142:1, 128–137

Bibliographic databases:

Received: 11.11.2003
Revised: 03.06.2004

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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\paper The problem of processing time series: Extending possibilities of the local approximation method using singular spectrum analysis
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\transl
\jour Theoret. and Math. Phys.
\yr 2005
\vol 142
\issue 1
\pages 128--137
\crossref{https://doi.org/10.1007/s11232-005-0077-y}
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  • https://doi.org/10.4213/tmf1771
  • http://mi.mathnet.ru/eng/tmf/v142/i1/p148

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    Citing articles on Google Scholar: Russian citations, English citations
    Related articles on Google Scholar: Russian articles, English articles

    This publication is cited in the following articles:
    1. A. Yu. Loskutov, “Fascination of chaos”, Phys. Usp., 53:12 (2010), 1257–1280  mathnet  crossref  crossref  isi  elib
    2. 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
    3. 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
    4. Krutikov V.N., Indenko O.N., Chernova E.S., 2018 International Scientific Multi-Conference on Industrial Engineering and Modern Technologies (Fareastcon), IEEE, 2018  isi
    5. 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
  • Теоретическая и математическая физика Theoretical and Mathematical Physics
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