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Iterated Tikhonov regularization of large linear problems
Davide Furchì, Lothar Reichel
Many solution methods for linear discrete ill-posed problems with error-contaminated data (right-hand side) apply Tikhonov regularization to compute a meaningful approximate soluti…
The iterated Golub-Kahan-Tikhonov method
Davide Bianchi, Marco Donatelli, Davide Furchì +1
The Golub-Kahan-Tikhonov method is a popular solution technique for large linear discrete ill-posed problems. This method first applies partial Golub-Kahan bidiagonalization to red…
Improved parameter selection strategy for the iterated Arnoldi-Tikhonov method
Marco Donatelli, Davide Furchì
The iterated Arnoldi-Tikhonov (iAT) method is a regularization technique particularly suited for solving large-scale ill-posed linear inverse problems. Indeed, it reduces the compu…
Convergence analysis and parameter estimation for the iterated Arnoldi-Tikhonov method
Davide Bianchi, Marco Donatelli, Davide Furchì +1
The Arnoldi-Tikhonov method is a well-established regularization technique for solving large-scale ill-posed linear inverse problems. This method leverages the Arnoldi decompositio…