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Avtomatika i Telemekhanika, 2014, Issue 5, Pages 83–90 (Mi at9095)  
This article is cited in 3 scientific papers (total in 3 papers)

Stochastic Systems, Queuing Systems

Estimating the characteristics of randomized dynamic data models (the 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 (696 kB) Citations (3)
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Abstract: We propose a new approach to finding dependencies between small volumes of input and output data based on randomized dynamic models and density estimation for the distributions of their parameters. Randomized dynamic models are defined by functional Volterra polynomials. To construct robust nonparametric estimation procedures, we develop an entropybased approach that employs functionals of generalized informational Boltzmann and Fermi entropies.
Presented by the member of Editorial Board: A. I. Kibzun

Received: 27.03.2013
English version:
Automation and Remote Control, 2014, Volume 75, Issue 5, Pages 872–879
DOI: https://doi.org/10.1134/S0005117914050063
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: Yu. S. Popkov, A. Yu. Popkov, Yu. N. Lysak, “Estimating the characteristics of randomized dynamic data models (the entropy-robust approach)”, Avtomat. i Telemekh., 2014, no. 5, 83–90; Autom. Remote Control, 75:5 (2014), 872–879
Citation in format AMSBIB
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\by Yu.~S.~Popkov, A.~Yu.~Popkov, Yu.~N.~Lysak
\paper Estimating the characteristics of randomized dynamic data models (the entropy-robust approach)
\jour Avtomat. i Telemekh.
\yr 2014
\issue 5
\pages 83--90
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\transl
\jour Autom. Remote Control
\yr 2014
\vol 75
\issue 5
\pages 872--879
\crossref{https://doi.org/10.1134/S0005117914050063}
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Linking options:
  • https://www.mathnet.ru/eng/at9095
  • https://www.mathnet.ru/eng/at/y2014/i5/p83
    • This publication is cited in the following 3 articles:
    1. 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
    2. 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
    3. 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
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
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    Full-text PDF :71
    References:51
    First page:22
     
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