The approximate inverse in action II: convergence and stability

DOI10.1090/S0025-5718-03-01526-6zbMath1022.65066WikidataQ60707586 ScholiaQ60707586MaRDI QIDQ4806394

Andreas Rieder, Thomas Schuster

Publication date: 14 May 2003

Published in: Mathematics of Computation (Search for Journal in Brave)

zbMATH Keywords

stabilityconvergenceregularizationHilbert spacestomographyapproximate inversemollificationfiltered back projection algorithmoperator equations of the first kindradon transform

Mathematics Subject Classification ID

Biomedical imaging and signal processing (92C55) Radon transform (44A12) Numerical methods for integral transforms (65R10) Numerical solutions to equations with linear operators (65J10) Equations and inequalities involving linear operators, with vector unknowns (47A50) 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)

Related Items (14)

Error estimates for defect correction methods in Doppler tomography ⋮ Error estimates and convergence rates for filtered back projection ⋮ Semi-discrete Tikhonov regularization in RKHS with large randomly distributed noise ⋮ Linear Functional Strategy and the Approximate Inverse for Nonlinear Ill-Posed Problems ⋮ Approximate Inversion of a Class of Generalized Radon Transforms ⋮ Approximate inverse for the common offset acquisition geometry in 2D seismic imaging ⋮ Error analysis for filtered back projection reconstructions in Besov spaces ⋮ Numerical rate function determination in partial differential equations modeling cell population dynamics ⋮ Two approaches to the problem of defect correction in vector field tomography solving boundary value problems ⋮ Finite dimensional realization of mollifier method: A new stable approach ⋮ A mollification regularization method for stable analytic continuation ⋮ A finite dimensional realization of the mollifier method for compact operator equations ⋮ A stable inversion scheme for the Laplace transform using arbitrarily distributed data scanning points ⋮ Saturation rates of filtered back projection approximations

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