Development of Fokker-Planck equations for stochastic dynamical systems modeled by Marcus stochastic differential equations

Fokker-Planck equations describe the time evolution of probability densities of stochastic dynamical systems and play an important role in quantifying propagation and evolution of uncertainty. Although Fokker-Planck equations are well established for nonlinear dynamical systems excited by Gaussian white noise, it is not available in general for nonlinear dynamical systems excited by non-Gaussian white noise. Marcus stochastic differential equations are often appropriate models in engineering and physics for stochastic dynamical systems excited by non-Gaussian white noise. This talk presents explicit forms of Fokker-Planck equations for Marcus stochastic differential equations. Examples are given to illustrate the theoretical results.

Event Topic

Stochastic & Multiscale Modeling and Computation