Journal of Inverse and Ill-posed Problems
Editor-in-Chief: Kabanikhin, Sergey I.
6 Issues per year
IMPACT FACTOR 2016: 0.783
5-year IMPACT FACTOR: 0.792
CiteScore 2016: 0.80
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Source Normalized Impact per Paper (SNIP) 2015: 1.106
Mathematical Citation Quotient (MCQ) 2015: 0.43
Discrepancy curves for multi-parameter regularization
For solving linear ill-posed problems regularization methods are required when the right-hand side is with some noise. In the present paper regularized solutions are obtained by multi-parameter regularization and the regularization parameters are chosen by a multi-parameter discrepancy principle. Under certain smoothness assumptions we provide order optimal error bounds that characterize the accuracy of the regularized solutions. For the computation of the regularization parameters fast algorithms of Newton type are applied which are based on special transformations. These algorithms are globally and monotonically convergent. Some of our theoretical results are illustrated by numerical experiments. We also show how the proposed approach may be employed for multi-task approximation.
Keywords.: Ill-posed problems; inverse problems; noisy right-hand side; Tikhonov regularization; multi-parameter regularization; discrepancy principle; order optimal error bounds; Newton's method; global convergence; monotone convergence
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