Non-Gaussian Random Processes Modeling Using Stochastic Differential Equations

This paper discusses an approach to modeling non-Gaussian random processes using Stochastic Differential Equations (SDE). It considers modeling of exponentially correlated random processes with an arbitrary probability density function. This type of process is used in a wide range of applications, including communications, radar, computer networks, and biology, but it can also be a building block for more complicated models. As an example, synthesis of compound processes with arbitrary rational power spectrum density is considered.