论文标题
超级线性系数的随机微分方程的不变度度量的向后欧拉玛雅语方法
The backward Euler-Maruyama method for invariant measures of stochastic differential equations with super-linear coefficients
论文作者
论文摘要
向后的Euler-Maruyama（BEM）方法用于近似随机微分方程的不变度度量，在该方程中，漂移和扩散系数都可以超级线性生长。证明了由BEM方法生成的数值解决方案的不变度度量的存在和唯一性，并显示了数值不变度度量与基础措施的收敛性。提供了模拟来说明理论结果，并证明了我们在系统控制领域的结果。
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.
