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Approximation accuracy of the Krylov subspaces for linear discrete ill-posed problems. (English) Zbl 1434.65043
The author makes a deep analysis on the regularizing effects of LSQR, thus establishing a general \(\sin(\Theta)\) theorem for the \(2\)-norm distances between these two subspaces and deriving accurate estimates on them for severely, moderately and mildly ill-posed problems.

65F22 Ill-posedness and regularization problems in numerical linear algebra
15A18 Eigenvalues, singular values, and eigenvectors
65F10 Iterative numerical methods for linear systems
65F20 Numerical solutions to overdetermined systems, pseudoinverses
65R32 Numerical methods for inverse problems for integral equations
65J20 Numerical solutions of ill-posed problems in abstract spaces; regularization
65J22 Numerical solution to inverse problems in abstract spaces
65R30 Numerical methods for ill-posed problems for integral equations
47A52 Linear operators and ill-posed problems, regularization
15A29 Inverse problems in linear algebra
45Q05 Inverse problems for integral equations
86A22 Inverse problems in geophysics
Full Text: DOI
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