rrgmrestbx
Algorithms for range restricted iterative methods for linear discrete ill-posed problems. Range restricted iterative methods based on the Arnoldi process are attractive for the solution of large nonsymmetric linear discrete ill-posed problems with error-contaminated data (right-hand side). Several derivations of this type of iterative methods are compared by the authors [Implementation of range restricted iterative methods for linear discrete ill-posed problems. Linear Algebra Appl (to appear)]. We describe MATLAB codes for the best of these implementations. MATLAB codes for range restricted iterative methods for symmetric linear discrete ill-posed problems are also presented. (netlib numeralgo na33)
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References in zbMATH (referenced in 10 articles , 1 standard article )
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- Bellalij, M.; Reichel, L.; Sadok, H.: Some properties of range restricted GMRES methods (2015)
- Donatelli, M.; Reichel, L.: Square smoothing regularization matrices with accurate boundary conditions (2014)
- Dykes, L.; Marcellán, F.; Reichel, L.: The structure of iterative methods for symmetric linear discrete ill-posed problems (2014)
- Hearn, Tristan A.; Reichel, Lothar: Application of denoising methods to regularizationof ill-posed problems (2014)
- Morikuni, Keiichi; Reichel, Lothar; Hayami, Ken: FGMRES for linear discrete ill-posed problems (2014)
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- Donatelli, Marco; Neuman, Arthur; Reichel, Lothar: Square regularization matrices for large linear discrete ill-posed problems. (2012)
- Neuman, Arthur; Reichel, Lothar; Sadok, Hassane: Algorithms for range restricted iterative methods for linear discrete ill-posed problems (2012)