Control, Accuracy and Reliability of a Statistical Simulation of Non-Stationary Systems

Abstract

Abstract The problem of control and estimating the reliability of a complex stochastic systems modelling is examined. In order to solve this problem the estimates of statistical characteristics of a random processes and fields are used. New method of computing the distribution function of spectral density and correlation function of random processes and fields is suggested. We discuss the new results in application of a curve estimates by Parzen and Rozenblatt to estimation the distribution density of random processes and fields. The effective and quasieffective estimates for variance and mathematical expectation of non-stationary processes are observed. New method of statistical simulation of multidimensional random fields, defined by spectral decomposition, is suggested. The numerical algorithms of a parametric modelling of some classes of random functions are considered.