Add to ORKGAbstract. Large linear discrete ill-posed problems with contaminated data are often solved with the aid of Tikhonov regularization. Commonly used regularization matrices are finite difference approximations of a suitable derivative and are rectangular. This paper discusses the design of square regularization matrices that can be used in iterative methods based on the Arnoldi process for large-scale Tikhonov regularization problems. Key words. Tikhonov regularization, regularization matrix, Arnoldi proces
Tikhonov regularization of linear discrete ill-posed problems often is applied with a finite differe...
AbstractTikhonov regularization for large-scale linear ill-posed problems is commonly implemented by...
Many problems in science and engineering give rise to linear systems of equations that are commonly ...
Large linear discrete ill-posed problems with contaminated data are often solved with the aid of Tik...
Large linear discrete ill-posed problems with contaminated data are often solved with the aid of Tik...
Large linear discrete ill-posed problems with contaminated data are often solved with the aid of Tik...
Large linear discrete ill-posed problems with contaminated data are often solved with the aid of Tik...
Large linear discrete ill-posed problems with contaminated data are often solved with the aid of Tik...
This paper is concerned with the solution of large-scale linear discrete ill-posed problems. The det...
This paper is concerned with the solution of large-scale linear discrete ill-posed problems. The det...
This paper is concerned with the solution of large-scale linear discrete ill-posed problems. The det...
This paper is concerned with the solution of large-scale linear discrete ill-posed problems. The det...
This paper is concerned with the solution of large-scale linear discrete ill-posed problems. The det...
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...
Tikhonov regularization of linear discrete ill-posed problems often is applied with a finite differe...
AbstractTikhonov regularization for large-scale linear ill-posed problems is commonly implemented by...
Many problems in science and engineering give rise to linear systems of equations that are commonly ...
Large linear discrete ill-posed problems with contaminated data are often solved with the aid of Tik...
Large linear discrete ill-posed problems with contaminated data are often solved with the aid of Tik...
Large linear discrete ill-posed problems with contaminated data are often solved with the aid of Tik...
Large linear discrete ill-posed problems with contaminated data are often solved with the aid of Tik...
Large linear discrete ill-posed problems with contaminated data are often solved with the aid of Tik...
This paper is concerned with the solution of large-scale linear discrete ill-posed problems. The det...
This paper is concerned with the solution of large-scale linear discrete ill-posed problems. The det...
This paper is concerned with the solution of large-scale linear discrete ill-posed problems. The det...
This paper is concerned with the solution of large-scale linear discrete ill-posed problems. The det...
This paper is concerned with the solution of large-scale linear discrete ill-posed problems. The det...
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...
Tikhonov regularization of linear discrete ill-posed problems often is applied with a finite differe...
AbstractTikhonov regularization for large-scale linear ill-posed problems is commonly implemented by...
Many problems in science and engineering give rise to linear systems of equations that are commonly ...