Chebyshevskii Sbornik
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Chebyshevskii Sb.:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Chebyshevskii Sb., 2016, Volume 17, Issue 1, Pages 240–253 (Mi cheb467)  

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

On the best linear method of approximation of some classes analytic functions in the weighted Bergman space

M. S. Saidusaynov

Tajik National University, Dushanbe

Abstract: In this paper the exact values of different widths in the space $B_{q,\gamma}$, $1\leq q\leq\infty$ with the weight $\gamma$ for classes $W_{q,a}^{(r)}(\Phi,\mu)$ were calculated. These classes is consist from functions $f$, which are analytic in a circle $U_{R}:=ż: |z|\leq R\}$ $(0<R\leq 1)$ whose $n (n\in\mathbb{N})$-th derivatives by argument $f_{a}^{(r)}$ is belong to the space $B_{q,\gamma} (1\leq q\leq\infty, 0<R\leq 1)$ and have an averaged modulus of smoothness of second order majorized by function $\Phi$, and everywhere further assumed that the function $\Phi(t), t>0$ is an arbitrary function that $\Phi(0)=0$.
The exact inequalities between the best polynomial approximation of analytic functions in a unit disk and integrals consisted from averaged modulus of smoothness of second order functions with $r$-th derivatives order and concrete weight which is flow out from substantial meaning of problem statement. The obtained result is guarantee to calculate the exact values of Bernshtein and Kolmogorov's widths. Method of approximation which is used for obtaining the estimation from above the Kolmogorov n-width is learn on L. V. Taykov work which earlier is proved for modulus of smoothness of complex polynomials.
The special interest is offer the problem about constructing the best linear methods of approximation of classes functions $W_{q,a}^{(r)}(\Phi,\mu)$ and connected to it the problem in calculating the exact values of Linear and Gelfand $n$-widths. The founded best linear methods is depend on given number $\mu\geq 1$ and in particular when $\mu=1$ is contain the previous proved results. Also showed the explicit form an optimal subspaces given dimension which are implement the values of widths.
Bibliography: 18 titles.

Keywords: the best linear method, $n$-widths, module of smoothness.

Full text: PDF file (703 kB)
References: PDF file   HTML file
UDC: 517.5
Received: 22.12.2015
Accepted:11.03.2016

Citation: M. S. Saidusaynov, “On the best linear method of approximation of some classes analytic functions in the weighted Bergman space”, Chebyshevskii Sb., 17:1 (2016), 240–253

Citation in format AMSBIB
\Bibitem{Sai16}
\by M.~S.~Saidusaynov
\paper On the best linear method of approximation of some classes analytic functions in the weighted Bergman space
\jour Chebyshevskii Sb.
\yr 2016
\vol 17
\issue 1
\pages 240--253
\mathnet{http://mi.mathnet.ru/cheb467}
\elib{https://elibrary.ru/item.asp?id=25795087}


Linking options:
  • http://mi.mathnet.ru/eng/cheb467
  • http://mi.mathnet.ru/eng/cheb/v17/i1/p240

    SHARE: VKontakte.ru FaceBook Twitter Mail.ru Livejournal Memori.ru


    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. Mukim S. Saidusajnov, “$\mathcal{K}$-functionals and exact values of $n$-widths in the Bergman space”, Ural Math. J., 3:2 (2017), 74–81  mathnet  crossref  mathscinet
    2. M. Sh. Shabozov, M. S. Saidusainov, “Srednekvadratichnoe priblizhenie funktsii kompleksnoi peremennoi ryadami Fure v vesovom prostranstve Bergmana”, Vladikavk. matem. zhurn., 20:1 (2018), 86–97  mathnet  crossref  elib
  • Number of views:
    This page:147
    Full text:50
    References:38

     
    Contact us:
     Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2021