A change of measure enhanced near exact Euler Maruyama scheme for the solution to nonlinear stochastic dynamical systems

Understand

The present study utilizes the Girsanov transformation based framework for solving a nonlinear stochastic dynamical system in an efficient way in comparison to other available approximate methods.

• In this approach, a rejection sampling is formulated to evaluate the Radon-Nikodym derivative arising from the change of measure due to Girsanov transformation.
• The rejection sampling is applied on the Euler Maruyama approximated sample paths which draw exact paths independent of the diffusion dynamics of the underlying dynamical system.
• The efficacy of the proposed framework is ensured using more accurate numerical as well as exact nonlinear methods.