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Bulletin of Irkutsk State University. Series Mathematics, 2020, Volume 31, Pages 78–95
DOI: https://doi.org/10.26516/1997-7670.2020.31.78
(Mi iigum407)
 

This article is cited in 1 scientific paper (total in 1 paper)

Integro-differential equations and functional analysis

Fractional smoothness of distributions of trigonometric polynomials on a space with a Gaussian measure

G. I. Zelenovab

a Moscow State University, Moscow, Russian Federation
b National Research University "Higher School of Economics", Moscow
Full-text PDF (413 kB) Citations (1)
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Abstract: In this paper we study properties of images of a gaussian measure under trigonometric polynomials of a fixed degree, defined on finite-dimensional space with fixed number of dimensions. We prove that the images of the $n$-dimensional Gaussian measure under trigonometric polynomials have densities from the Nikolskii–Besov class of fractional parameter. This property of images of a gaussian measure is used for estimating the total variation distance between such images via the Fortet–Mourier distance. We also generalize these results to the case of $k$-dimensional mappings whose components are trigonometric polynomials.
Keywords: Nikolskii–Besov class, Gaussian measure, distribution of a trigonometric polynomial.
Funding agency Grant number
Russian Science Foundation 17-11-01058
Received: 27.11.2019
Bibliographic databases:
Document Type: Article
UDC: 519.2
MSC: Primary 60E05, 60E015; Secondary 28C20, 60F99
Language: Russian
Citation: G. I. Zelenov, “Fractional smoothness of distributions of trigonometric polynomials on a space with a Gaussian measure”, Bulletin of Irkutsk State University. Series Mathematics, 31 (2020), 78–95
Citation in format AMSBIB
\Bibitem{Zel20}
\by G.~I.~Zelenov
\paper Fractional smoothness of distributions of trigonometric polynomials on a space with a Gaussian measure
\jour Bulletin of Irkutsk State University. Series Mathematics
\yr 2020
\vol 31
\pages 78--95
\mathnet{http://mi.mathnet.ru/iigum407}
\crossref{https://doi.org/10.26516/1997-7670.2020.31.78}
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  • https://www.mathnet.ru/eng/iigum/v31/p78
  • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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    Full-text PDF :66
    References:32
     
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