In this paper we consider new regularization methods for linear inverse problems of dynamic type. These methods are based on dynamic programming techniques for linear quadratic optimal control problems. Two different approaches are followed: a continuous and a discrete one. We prove regularization properties and also obtain rates of convergence for the methods derived from both approaches. A numerical example concerning the dynamic EIT problem is used to illustrate the theoretical results.

翻译：在本文中,我们考虑对动态类型的线性反问题采用新的正规化方法,这些方法以线性二次最佳控制问题的动态编程技术为基础,采取两种不同的做法:一种是连续的,一种是独立的。我们证明正规化的特性,两种方法产生的方法也取得趋同率。用一个动态经济转型期问题的数字例子来说明理论结果。