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Avtomatika i Telemekhanika, 2013, Issue 11, Pages 114–131 (Mi at6164)  
This article is cited in 6 scientific papers (total in 6 papers)

System Analysis and Operations Research

Estimation of characteristics of randomized static models of data (entropy-robust approach)

Yu. S. Popkov, A. Yu. Popkov, Yu. N. Lysak

Institute for Systems Analysis, Russian Academy of Sciences, Moscow, Russia
Full-text PDF (2243 kB) Citations (6)
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Abstract: A new approach to the definition of static relations between small amounts of input and output data is suggested, which is based on the use of randomized models and the estimation of probability characteristics of their parameters. To work up the procedures of robust parametric and nonparametric estimation, the entropy approach is developed, which uses generalized Boltzmann and Fermi informational entropies.
Presented by the member of Editorial Board: B. T. Polyak

Received: 27.11.2012
English version:
Automation and Remote Control, 2013, Volume 74, Issue 11, Pages 1863–1877
DOI: https://doi.org/10.1134/S0005117913110088
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: Yu. S. Popkov, A. Yu. Popkov, Yu. N. Lysak, “Estimation of characteristics of randomized static models of data (entropy-robust approach)”, Avtomat. i Telemekh., 2013, no. 11, 114–131; Autom. Remote Control, 74:11 (2013), 1863–1877
Citation in format AMSBIB
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\paper Estimation of characteristics of randomized static models of data (entropy-robust approach)
\jour Avtomat. i Telemekh.
\yr 2013
\issue 11
\pages 114--131
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\transl
\jour Autom. Remote Control
\yr 2013
\vol 74
\issue 11
\pages 1863--1877
\crossref{https://doi.org/10.1134/S0005117913110088}
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Linking options:
  • https://www.mathnet.ru/eng/at6164
  • https://www.mathnet.ru/eng/at/y2013/i11/p114
    • This publication is cited in the following 6 articles:
    1. Yu. S. Popkov, “Analytic Method for Solving One Class of Nonlinear Equations”, Dokl. Math., 2024  crossref
    2. Svetlana Solodusha, Yuliya Kokonova, Oksana Dudareva, “Integral Models in the Form of Volterra Polynomials and Continued Fractions in the Problem of Identifying Input Signals”, Mathematics, 11:23 (2023), 4724  crossref
    3. Yu. S. Popkov, Yu. A. Dubnov, “Entropy-robust randomized forecasting under small sets of retrospective data”, Autom. Remote Control, 77:5 (2016), 839–854  mathnet  crossref  isi  elib  elib
    4. Cai Zh., Zhang Yu., Wu M., Cai D., “An Entropy-Robust Optimization of Mobile Commerce System Based on Multi-Agent System”, Arab. J. Sci. Eng., 41:9 (2016), 3703–3715  crossref  isi  elib  scopus
    5. Y. S. Popkov, A. Y. Popkov, B. S. Darkhovskiy, “Parallel Monte Carlo for entropy-robust estimation”, Math. Models Comput. Simul., 8:1 (2016), 27–39  mathnet  crossref  mathscinet  elib
    6. Yu. S. Popkov, A. Yu. Popkov, Yu. N. Lysak, “Estimating the characteristics of randomized dynamic data models (the entropy-robust approach)”, Autom. Remote Control, 75:5 (2014), 872–879  mathnet  crossref  isi
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
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    References:71
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