Numerical methods for ordinary differential systems: the initial value problem
Numerical methods for ordinary differential systems: the initial value problem
Stability Analysis of Numerical Schemes for Stochastic Differential Equations
SIAM Journal on Numerical Analysis
Runge-Kutta methods for numerical solution of stochastic differential equations
Journal of Computational and Applied Mathematics
Weak Second Order Conditions for Stochastic Runge--Kutta Methods
SIAM Journal on Scientific Computing
Mean-Square and Asymptotic Stability of the Stochastic Theta Method
SIAM Journal on Numerical Analysis
Mean-square stability of second-order Runge-Kutta methods for stochastic differential equations
Journal of Computational and Applied Mathematics
Convergence and stability of the split-step θ-method for stochastic differential equations
Computers & Mathematics with Applications
Mathematics and Computers in Simulation
SIAM Journal on Numerical Analysis
Applied Numerical Mathematics
Stabilized multilevel Monte Carlo method for stiff stochastic differential equations
Journal of Computational Physics
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In this paper, the mean-square stability of second-order Runge-Kutta schemes for multi-dimensional linear stochastic differential systems is studied. Motivated by the work of Tocino [Mean-square stability of second-order Runge-Kutta methods for stochastic differential equations, J. Comput. Appl. Math. 175 (2005) 355-367] and Saito and Mitsui [Mean-square stability of numerical schemes for stochastic differential systems, in: International Conference on SCIentific Computation and Differential Equations, July 29-August 3 2001, Vancouver, British Columbia, Canada] we investigate the mean-square stability of second-order Runge-Kutta schemes for multi-dimensional linear stochastic differential systems with one multiplicative noise. Stability criteria are established and numerical examples that confirm the theoretical results are also presented.