Ill-posed problems and the conjugate gradient method: optimal convergence rates in the presence of discretization and modelling errors

DOI10.1515/jiip-2022-0039OpenAlexW4308363186MaRDI QIDQ2101122

Andreas Neubauer

Publication date: 28 November 2022

Published in: Journal of Inverse and Ill-Posed Problems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/jiip-2022-0039

zbMATH Keywords

discrepancy principleill-posed problemsconjugate gradient

Mathematics Subject Classification ID

Numerical methods for ill-posed problems for integral equations (65R30) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20) Linear operators and ill-posed problems, regularization (47A52)

Cites Work

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• An a posteriori parameter choice for Tikhonov regularization in the presence of modeling error
• Erratum to: ``Optimal convergence rates for inexact Newton regularization with CG as inner iteration
• Optimal convergence rates for inexact Newton regularization with CG as inner iteration
• The regularizing properties of the adjoint gradient method in ill-posed problems
• Augmented GMRES-type versus CGNE methods for the solution of linear ill-posed problems

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