Stochastic multi-symplectic Runge–Kutta methods for stochastic Hamiltonian PDEs
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DOI: 10.1016/j.apnum.2018.09.011
Abstract: In this paper, we consider stochastic Runge-Kutta methods for stochastic Hamiltonian partial differential equations and present some sufficient conditions for multisymplecticity of stochastic Runge-Kutta methods of stochastic Hamiltonian partial differential equations. Particularly, we apply these… read more here.
Keywords: runge kutta; methods stochastic; kutta methods; multi symplectic ... See more keywords
Projection methods for stochastic dynamic systems: A frequency domain approach
Sign Up to like & getrecommendations! Published in 2018 at "Computer Methods in Applied Mechanics and Engineering"
DOI: 10.1016/j.cma.2018.04.025
Abstract: Abstract A collection of hybrid projection approaches are proposed for approximating the response of stochastic partial differential equations which describe structural dynamic systems. In this study, an optimal basis for the approximation of the response… read more here.
Keywords: projection methods; hybrid projection; methods stochastic; approach ... See more keywords
Mean-Square Stability of Split-Step Theta Milstein Methods for Stochastic Differential Equations
Sign Up to like & getrecommendations! Published in 2018 at "Mathematical Problems in Engineering"
DOI: 10.1155/2018/1682513
Abstract: The fundamental analysis of numerical methods for stochastic differential equations (SDEs) has been improved by constructing new split-step numerical methods. In this paper, we are interested in studying the mean-square (MS) stability of the new… read more here.
Keywords: methods stochastic; step; stochastic differential; split step ... See more keywords