This article is cited in 9 papers

Approximate models of random processes and fields

G. A. Mikhailov

Novosibirsk

Abstract: A class of models of stochastic processes and fields with a convex correlation function and a given one-dimensional distribution is constructed on the basis of stationary point flows. It is sometimes possible to improve successively the multi-dimensional distributions by using the summability of the realizations, the convergence being weak for non-negative processes. The convergence of approximate models of Gaussian fields, obtained by special randomization of the spectral resolution, is studied. The models can be realized quite easily on a computer.

UDC: 519.676

Received: 25.06.1981
Revised: 05.01.1982

 English version: USSR Computational Mathematics and Mathematical Physics, 1983, 23:3, 28–33

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