The backward Euler-Maruyama method for invariant measures of stochastic differential equations with super-linear coefficients
Copyright policy )The backward Euler-Maruyama method for invariant measures of stochastic differential equations with super-linear coefficients
The backward Euler-Maruyama (BEM) method is employed to approximate the invariant measure of stochastic differential equations, where both the drift and the diffusion coefficient are allowed to grow super-linearly. The existence and uniqueness of the invariant measure of the numerical solution generated by the BEM method are proved and the convergence of the numerical invariant measure to the underlying one is shown. Simulations are provided to illustrate the theoretical results and demonstrate the application of our results in the area of system control.
- University of Strathclyde United Kingdom
- Shanghai Normal University China (People's Republic of)
65C30, 65L20, 60H10, Probability (math.PR), backward Euler-Maruyama method, Probabilistic methods, stochastic differential equations, stationary measure, Numerical Analysis (math.NA), stochastic differential equation, implicit method, 510, FOS: Mathematics, Numerical methods for ordinary differential equations, Mathematics - Numerical Analysis, Mathematics, Computational methods for stochastic equations (aspects of stochastic analysis), super-linear coefficients, Mathematics - Probability
65C30, 65L20, 60H10, Probability (math.PR), backward Euler-Maruyama method, Probabilistic methods, stochastic differential equations, stationary measure, Numerical Analysis (math.NA), stochastic differential equation, implicit method, 510, FOS: Mathematics, Numerical methods for ordinary differential equations, Mathematics - Numerical Analysis, Mathematics, Computational methods for stochastic equations (aspects of stochastic analysis), super-linear coefficients, Mathematics - Probability
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