Computational Aspects of a Method of Stochastic Approximation

  • Konstantin V. Runovski

    Lomonosov State University, Sevastopol, Ukraine
  • Igor Rystsov

    National Technical University, Kiev, Ukraine
  • Hans-Jürgen Schmeisser

    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 Maple are discussed. It is shown that the algorithm can be applied not only to problems of “pure approximation” in the spaces with , but also to problems of signal processing, especially, if one is interested in strong oscillating data or data containing an essential stochastic item.

Cite this article

Konstantin V. Runovski, Igor Rystsov, Hans-Jürgen Schmeisser, Computational Aspects of a Method of Stochastic Approximation. Z. Anal. Anwend. 25 (2006), no. 3, pp. 367–383

DOI 10.4171/ZAA/1294