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Avtomat. i Telemekh., 1983, Issue 10, Pages 119–127 (Mi at5233)  

This article is cited in 2 scientific papers (total in 2 papers)

Adaptive Systems

On strong convergence of the method of least squares

A. E. Barabanov

Leningrad

Abstract: An unknown vector-valued parameter is estimated from its linear combination in the presence of additive white noise. The factors of the unknowns depend on the past history. The properties of convergence with a probability of 1 of the estimates are found by the method of least squares.

Full text: PDF file (1312 kB)

English version:
Automation and Remote Control, 1983, 44:10, 1338–1346

Bibliographic databases:

Document Type: Article
UDC: 519.281.2
Received: 07.01.1982

Citation: A. E. Barabanov, “On strong convergence of the method of least squares”, Avtomat. i Telemekh., 1983, no. 10, 119–127; Autom. Remote Control, 44:10 (1983), 1338–1346

Citation in format AMSBIB
\Bibitem{Bar83}
\by A.~E.~Barabanov
\paper On strong convergence of the method of least squares
\jour Avtomat. i Telemekh.
\yr 1983
\issue 10
\pages 119--127
\mathnet{http://mi.mathnet.ru/at5233}
\mathscinet{http://www.ams.org/mathscinet-getitem?mr=748190}
\zmath{https://zbmath.org/?q=an:0551.93071}
\transl
\jour Autom. Remote Control
\yr 1983
\vol 44
\issue 10
\pages 1338--1346


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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. V. Melnikov, “Stochastic differential equations: singularity of coefficients, regression models, and stochastic approximation”, Russian Math. Surveys, 51:5 (1996), 819–909  mathnet  crossref  crossref  mathscinet  zmath  adsnasa  isi
    2. A. E. Barabanov, Yu. R. Gel', “Convergence of the least-squares method with a polynomial regularizer for the infinite-dimensional autoregression equation”, Autom. Remote Control, 66:1 (2005), 92–107  mathnet  crossref  mathscinet  zmath
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