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Zeitschrift für Analysis und ihre Anwendungen

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Volume 25, Issue 3, 2006, pp. 367–383
DOI: 10.4171/ZAA/1294

Published online: 2006-09-30

Computational Aspects of a Method of Stochastic Approximation

Konstantin V. Runovski[1], Igor Rystsov and Hans-Jürgen Schmeisser[2]

(1) Lomonosov State University, Sevastopol, Ukraine
(2) Friedrich-Schiller-University, Jena, Germany

A method of stochastic approximation is studied in the framework of the general convergence theory for families of linear polynomial operators of interpolation type. The description of the corresponding computational procedure, in particular, its input parameters, is given. Some optimization problems and aspects of implementation of the algorithm by means of {\it Maple} are discussed. It is shown that the algorithm can be applied not only to problems of "pure approximation" in the spaces $\,L_p\,$ with $\,0

Keywords: Fast Fourier transform, random numbers, families of linear polynomial operators, approximation algorithms

Runovski Konstantin, Rystsov Igor, Schmeisser Hans-Jürgen: Computational Aspects of a Method of Stochastic Approximation. Z. Anal. Anwend. 25 (2006), 367-383. doi: 10.4171/ZAA/1294