Change of Measure Enhanced Near-Exact Euler–Maruyama Scheme for the Solution to Nonlinear Stochastic Dynamical Systems

The present study utilizes the Girsanov transformation-based framework for solving a nonlinear stochastic dynamical system in an efficient way comparison with other available approximate methods. In this approach, rejection sampling is formulated to evaluate Radon–Nikodym derivative arising from change of measure due transformation. Rejection applied on Euler–Maruyama approximated sample paths, which draw exact paths independent diffusion dynamics underlying system. efficacy proposed was ensured using more accurate numerical as well Finally, test problems were considered confirm theoretical results. demonstrated that formulation provides almost approximation both displacement and velocity states second-order