Enriched Krylov subspace methods for ill-posed problems

DOI10.1016/S0024-3795(02)00533-5zbMath1017.65025OpenAlexW2038616579MaRDI QIDQ1863587

A. Shuibi, Daniela Calvetti, Lothar Reichel

Publication date: 11 March 2003

Published in: Linear Algebra and its Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0024-3795(02)00533-5

zbMATH Keywords

numerical examplesconjugate gradient methodTikhonov regularization

Mathematics Subject Classification ID

Ill-posedness and regularization problems in numerical linear algebra (65F22) Iterative numerical methods for linear systems (65F10)

Related Items (8)

Exploiting compression in solving discretized linear systems ⋮ IR tools: a MATLAB package of iterative regularization methods and large-scale test problems ⋮ A survey of subspace recycling iterative methods ⋮ Hybrid Projection Methods with Recycling for Inverse Problems ⋮ A generalized LSQR algorithm ⋮ Decomposition methods for large linear discrete ill-posed problems ⋮ Augmented GMRES-type versus CGNE methods for the solution of linear ill-posed problems ⋮ Hybrid Projection Methods with Recycling for Inverse Problems

Uses Software

• Regularization tools
• TOMS-686
• RestoreTools

Cites Work

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• Regularization methods for large-scale problems
• Regularization tools: A Matlab package for analysis and solution of discrete ill-posed problems
• Quasi-Newton approach to nonnegative image restorations
• The Use of Auto-correlation for Pseudo-rank Determination in Noisy III-conditioned Linear Least-squares Problems
• Reorthogonalization and Stable Algorithms for Updating the Gram-Schmidt QR Factorization
• Fast CG-Based Methods for Tikhonov--Phillips Regularization
• Algorithm 686: FORTRAN subroutines for updating the QR decomposition
• Methods of conjugate gradients for solving linear systems

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