Tikhonov regularization is a cornerstone technique in solving inverse problems with
applications in countless scientific fields. Richard Huber discusses a multi-parameter Tikhonov
approach for systems of inverse problems in order to take advantage of their specific
structure. Such an approach allows to choose the regularization weights of each subproblem
individually with respect to the corresponding noise levels and degrees of ill-posedness.
