Accuracy estimates of regularization methods and conditional well-posedness of nonlinear optimization problems

DOI10.1515/JIIP-2017-0031OpenAlexW2799785423MaRDI QIDQ1755906

Xianqiang Yang

Publication date: 11 January 2019

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-2017-0031

zbMATH Keywords

Hilbert spaceregularizing operatoraccuracy estimateconvex closed setill-posed optimization problemerror levelBakushinsky vetoconditional well-posedness

Mathematics Subject Classification ID

Iterative procedures involving nonlinear operators (47J25) Nonlinear ill-posed problems (47J06) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20) Numerical solution to inverse problems in abstract spaces (65J22)

Cites Work

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• Necessary and sufficient conditions for power convergence rate of approximations in Tikhonov's scheme for solving ill-posed optimization problems
• Convergence rate estimates for Tikhonov's scheme as applied to ill-posed nonconvex optimization problems
• Stable approximation schemes for ill-posed convex variational problems
• On a characteristic property of conditionally well-posed problems
• Conditionally well-posed and generalized well-posed problems

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