中文摘要：

这份报纸为被 Brownian 运动和独立泊松随机两个都驾驶的随机的系统测量的提交向后学习部分观察的最佳的控制的问题。联合提交向后有某些古典凸的变化技术的随机的微分方程理论，必要最大的原则为部分观察的最佳的控制被证明，在控制域是 nonempty 的地方凸的集合。在某些凸状假设下面，作者也为上述的最佳的最佳的问题给最佳的控制的足够的条件。说明理论结果，作者也得出部分信息的一个例子线性二次的最佳的控制，并且由使用必要、足够的最大的原则发现相应最佳的控制的明确的表情。

英文摘要：

This paper studies the problem of partially observed optimal control for forward-backward stochastic systems which are driven both by Brownian motions and an independent Poisson random measure. Combining forward-backward stochastic differential equation theory with certain classical convex variational techniques, the necessary maximum principle is proved for the partially observed optimal control, where the control domain is a nonempty convex set. Under certain convexity assumptions, the author also gives the sufficient conditions of an optimal control for the aforementioned optimal optimal problem. To illustrate the theoretical result, the author also works out an example of partial information linear-quadratic optimal control, and finds an explicit expression of the corresponding optimal control by applying the necessary and sufficient maximum principle.