On regularizing effects of MINRES and MR-II for large scale symmetric discrete ill-posed problems

DOI10.1016/j.cam.2017.02.008zbMath1372.65119arXiv1503.03936OpenAlexW2314586021MaRDI QIDQ2400321

Yanyan Li

Publication date: 28 August 2017

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1503.03936

zbMATH Keywords

regularizationsingular value decompositionnumerical experimentKrylov subspacesemi-convergencefull regularizationpartial regularizationsymmetric ill-posed problem

Mathematics Subject Classification ID

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

Related Items (3)

Krylov methods for inverse problems: Surveying classical, and introducing new, algorithmic approaches ⋮ Regularization properties of LSQR for linear discrete ill-posed problems in the multiple singular value case and best, near best and general low rank approximations ⋮ The regularizing properties of global GMRES for solving large-scale linear discrete ill-posed problems with several right-hand sides

Uses Software

• LSQR
• Regularization tools
• UTV
• CRAIG

Cites Work

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• Matrix Algorithms
• LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
• Solution of Sparse Indefinite Systems of Linear Equations
• Approximate solutions and eigenvalue bounds from Krylov subspaces
• Restoration of atmospherically blurred images by symmetric indefinite conjugate gradient techniques
• Iterative Regularization and MINRES
• Discrete Inverse Problems

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