Using a Stochastic Differential Equations to Form of Non-Gaussian Random Processes. Part 1

The formation of non-Gaussian random processes by using stochastic differential equations is described. Algorithms for the formation of scalar continuousvalued, vector and discrete processes, as well as multi-linked sequences are presented. The analysis of the forming filter with parametric noise is carried out. The block diagram of the named filter is given. It is shown that the choice of parameters of input influences of the forming filter allows receiving an output signal with density of distribution of probabilities of Pearson family. It is also shown that in systems with parametric noise the probability density of the output variables is not Gaussian.