Tikhonov regularization is a cornerstone technique in solving inverse problems with applications in countless scienti c elds. Richard Huber discusses a multi-parameter Tikhonov approach for systems of inverse problems in order to take advantage of their speci c 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.
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Tikhonov regularization is a cornerstone technique in solving inverse problems with applications in countless scienti c elds. Richard Huber discusses a multi-parameter Tikhonov approach for systems of inverse problems in order to take advantage of their speci c 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.
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