Stochastic dynamical systems are fundamental in state estimation, system
identification and control. System models are often provided in continuous
time, while a major part of the applied theory is developed for discrete-time
systems. Discretization of continuous-time models is hence fundamental. We
present a novel algorithm using a combination of Lyapunov equations and
analytical solutions, enabling efficient implementation in software. The
proposed method circumvents numerical problems exhibited by standard algorithms
in the literature. Both theoretical and simulation results are provided
