Enhancing linear regularization to treat large noise

DOI10.1515/JIIP.2011.052zbMath1279.65071OpenAlexW2324577603MaRDI QIDQ5745486

Peter Mathé, Ulrich Tautenhahn

Publication date: 30 January 2014

Published in: jiip (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/jiip.2011.052

zbMATH Keywords

regularizationinverse problemsill-posed problemsHilbert scalessmall noiseorder optimal error boundslarge noise

Mathematics Subject Classification ID

Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20) Linear operators and ill-posed problems, regularization (47A52)

Related Items (3)

Fractional Tikhonov regularization with a nonlinear penalty term ⋮ Tikhonov regularization with oversmoothing penalty for non-linear ill-posed problems in Hilbert scales ⋮ Oracle-type posterior contraction rates in Bayesian inverse problems

Cites Work

• On the generalized discrepancy principle for Tikhonov regularization in Hilbert scales
• Conjugate gradient regularization under general smoothness and noise assumptions
• Regularization under general noise assumptions
• Interpolation in variable Hilbert scales with application to inverse problems
• On weakly bounded noise in ill-posed problems

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