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Matematicheskoe modelirovanie, 2020, Volume 32, Number 4, Pages 116–130
DOI: https://doi.org/10.20948/mm-2020-04-09 (Mi mm4176) 		 
This article is cited in 10 scientific papers (total in 10 papers)

Statistical method of recognizing on the base of nonlinear regression

B. M. Gavrikova, M. B. Gavrikovb, N. V. Pestryakovac

a Moscow State Budgetary Healthcare Institution "Moscow City Oncology Hospital No. 62 of the Moscow City Healthcare Department"
b Federal Research Center "Keldysh Institute of Applied Mathematics" of RAS, Moscow
c Federal Research Center "Computer Science and Control" of RAS, Moscow
Full-text PDF (364 kB) Citations (10)
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DOI: https://doi.org/10.20948/mm-2020-04-09
Abstract: The work is devoted to the statistical method of classification based on nonlinear regression. The ways of its implementation in solving the problem of recognition of printed and handwritten characters, as well as for the first time for assessing the health of the systems of the human body according to the parameters of peripheral blood. The optimal structure of polynomials is proposed. The properties of the probability estimates generated by the method are described. The structure of the sets used for its training is analyzed.
Keywords: recognition, classification, statistical method, polynomial regression, printed symbol, handwritten symbol, human health condition, body system, peripheral blood.
Received: 21.10.2019
Revised: 21.10.2019
Accepted: 25.11.2019
English version:
Mathematical Models and Computer Simulations, 2020, Volume 12, Issue 6, Pages 996–1004
DOI: https://doi.org/10.1134/S2070048220060083
Document Type: Article
Language: Russian
Citation: B. M. Gavrikov, M. B. Gavrikov, N. V. Pestryakova, “Statistical method of recognizing on the base of nonlinear regression”, Matem. Mod., 32:4 (2020), 116–130; Math. Models Comput. Simul., 12:6 (2020), 996–1004
Citation in format AMSBIB
\Bibitem{GavGavPes20}
\by B.~M.~Gavrikov, M.~B.~Gavrikov, N.~V.~Pestryakova
\paper Statistical method of recognizing on the base of nonlinear regression
\jour Matem. Mod.
\yr 2020
\vol 32
\issue 4
\pages 116--130
\mathnet{http://mi.mathnet.ru/mm4176}
\crossref{https://doi.org/10.20948/mm-2020-04-09}
\transl
\jour Math. Models Comput. Simul.
\yr 2020
\vol 12
\issue 6
\pages 996--1004
\crossref{https://doi.org/10.1134/S2070048220060083}
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    • This publication is cited in the following 10 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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