Solution of the Cauchy problem using iterated Tikhonov regularization

We are interested in this paper in recovering lacking data on some part of a domain boundary, from the knowledge of Cauchy data on the other part. It is first proved that the desired solution is the unique fixed point of some appropriate operator, which naturally gives rise to an iterative process that is proved to be convergent. Discretization provides an additional regularization: the algorithm reads as a least square fitting of the given data, with a regularization term the effect of which fades as iterations go on. Displayed numerical results highlight its accuracy, as well as its robustness.