In the present work, we study the determination of the regularization parameter and the computation of the regularized solution in Tikhonov regularization, by the Aitken's extrapolation method. In particular, this convergence acceleration method is adjusted for the approximation of quadratic forms that appear in regularization methods, such as the generalized cross-validation method, the quasi-optimality criterion, the Gfrerer/Raus method and the Morozov's discrepancy principle. We present several numerical examples to illustrate the effectiveness of the derived estimates for approximating the regularization parameter for several linear discrete ill-posed problems and we compare the described method with further existing methods, ...
Tikhonov regularization is one of the most popular approaches to solve discrete ill-posed problems w...
For the solution of linear discrete ill-posed problems, in this paper we consider the Arnoldi-Tikhon...
The straightforward solution of discrete ill-posed linear systems of equations or least-squares prob...
We consider regularization of linear ill‐posed problem Au = f with noisy data fδ, ¦fδ...
Tikhonov regularization is one of the most popular methods for computing an approximate solution of ...
Tikhonov regularization is one of the most popular methods for computing an approximate solution of ...
This paper introduces a new strategy for setting the regularization parameter when solving large-sca...
This paper introduces a new strategy for setting the regularization parameter when solving large-sca...
AbstractWe propose a method for choosing the regularization parameter in iterated Tikhonov regulariz...
Tikhonov regularization is one of the most popular approaches to solve discrete ill-posed problems w...
Tikhonov regularization is one of the most popular approaches to solve discrete ill-posed problems w...
The most commonly used method for the solution of ill-posed problems is Tikhonov regularization meth...
We present a discrepancy-based parameter choice and stopping rule for iterative algorithms performin...
For the solution of linear discrete ill-posed problems, in this paper we consider the Arnoldi-Tikhon...
Tikhonov regularization is one of the most popular approaches to solve discrete ill-posed problems w...
Tikhonov regularization is one of the most popular approaches to solve discrete ill-posed problems w...
For the solution of linear discrete ill-posed problems, in this paper we consider the Arnoldi-Tikhon...
The straightforward solution of discrete ill-posed linear systems of equations or least-squares prob...
We consider regularization of linear ill‐posed problem Au = f with noisy data fδ, ¦fδ...
Tikhonov regularization is one of the most popular methods for computing an approximate solution of ...
Tikhonov regularization is one of the most popular methods for computing an approximate solution of ...
This paper introduces a new strategy for setting the regularization parameter when solving large-sca...
This paper introduces a new strategy for setting the regularization parameter when solving large-sca...
AbstractWe propose a method for choosing the regularization parameter in iterated Tikhonov regulariz...
Tikhonov regularization is one of the most popular approaches to solve discrete ill-posed problems w...
Tikhonov regularization is one of the most popular approaches to solve discrete ill-posed problems w...
The most commonly used method for the solution of ill-posed problems is Tikhonov regularization meth...
We present a discrepancy-based parameter choice and stopping rule for iterative algorithms performin...
For the solution of linear discrete ill-posed problems, in this paper we consider the Arnoldi-Tikhon...
Tikhonov regularization is one of the most popular approaches to solve discrete ill-posed problems w...
Tikhonov regularization is one of the most popular approaches to solve discrete ill-posed problems w...
For the solution of linear discrete ill-posed problems, in this paper we consider the Arnoldi-Tikhon...
The straightforward solution of discrete ill-posed linear systems of equations or least-squares prob...