Generalized Wiener Process and Kolmogorov’s Equation for Diffusion Induced by Non-gaussian Noise Source

We show that the increments of generalized Wiener process, useful to describe nonGaussian white noise sources, have the properties of infinitely divisible random processes. Using functional approach and the new correlation formula for non-Gaussian white noise we derive directly from Langevin equation, with such a random source, the Kolmogorov’s equation for Markovian non-Gaussian process. From this equation we obtain the FokkerPlanck equation for nonlinear system driven by white Gaussian noise, the KolmogorovFeller equation for discontinuous Markovian processes, and the fractional Fokker-Planck equation for anomalous diffusion. The stationary probability distributions for some simple cases of anomalous diffusion are derived.