论文标题
通过Girsanov和Quasi Doob对称性减少和重建SDE
Reduction and reconstruction of SDEs via Girsanov and quasi Doob symmetries
论文作者
论文摘要
提出了基于随机对称性（包括Girsanov随机转换）的随机分化方程的还原程序。在这种情况下，给出了重建的新概念，涉及解决方案对SDE的函数的期望值，并证明了通用随机对称性的重建定理。此外，提出了在准DOOB转换的封闭子类下的显着减少情况。理论结果应用于应用中相关的随机模型。
A reduction procedure for stochastic differential equations based on stochastic symmetries including Girsanov random transformations is proposed. In this setting, a new notion of reconstruction is given, involving the expectation values of functionals of solution to the SDE and a reconstruction theorem for general stochastic symmetries is proved. Moreover, the notable case of reduction under the closed subclass of quasi Doob transformations is presented. The theoretical results are applied to stochastic models relevant in the applications.
