On weakly bounded noise in ill-posed problems

DOI10.1088/0266-5611/25/11/115018zbMath1191.65056OpenAlexW1977344462MaRDI QIDQ3652585

Paul P. B. Eggermont, Vincent N. La Riccia, M. Zuhair Nashed

Publication date: 18 December 2009

Published in: Inverse Problems (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/f86838d636639566b5f8863bbaa9785c4ed6a5e5

zbMATH Keywords

weak convergencenoisy dataHilbert spacesTikhonov regularizationill-posed problemscompact operator equationsLepskii methodweakly bounded noise

Mathematics Subject Classification ID

Numerical solutions to equations with linear operators (65J10) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20) Linear operators and ill-posed problems, regularization (47A52)

Related Items (9)

Operator-theoretic and regularization approaches to ill-posed problems ⋮ Fredholm integral equations of the first kind and topological information theory ⋮ Heuristic Parameter Choice Rules for Tikhonov Regularization with Weakly Bounded Noise ⋮ A new \textit{a posteriori} parameter choice strategy for the convolution regularization of the space-fractional backward diffusion problem ⋮ A fast algorithm for the inversion of Abel's transform ⋮ Incremental projection approach of regularization for inverse problems ⋮ Moment discretization for ill-posed problems with discrete weakly bounded noise ⋮ Enhancing linear regularization to treat large noise ⋮ Ill-Posed Problems: Operator Methodologies of Resolution and Regularization

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