Add to ORKGThe aim of this thesis is to study and describe regularizing properties of iterative Krylov subspace methods for finding a solution of linear algebraic ill- posed problems contaminated by white noise. First we explain properties of this kind of problems, especially their sensitivity to small perturbations in data. It is shown that classical methods for solving approximation problems (such as the least squares method) fail here. Thus we turn to explanation of regularizing pro- perties of projections onto Krylov subspaces. Basic Krylov regularizing methods are considered, namely RRGMRES, CGLS, and LSQR. The results are illustrated on model problems from Regularization toolbox in MATLAB.
Iterative Krylov subspace methods have proven to be efficient tools for solving linear systems of eq...
In this paper we present three theorems which give insight into the regularizing properties of MINRE...
The aim of this thesis is to study hybrid methods for solving ill-posed linear inverse problems corr...
Krylov subspace iterative methods have recently received considerable attention as regularizing tec...
Krylov subspace iterative methods have recently received considerable attention as regularizing tech...
In this thesis we consider a linear inverse problem Ax ≈ b with a smoothing operator A and a right-h...
The aim of this thesis is to study hybrid methods for solving ill-posed linear inverse problems corr...
The diploma thesis deals with the construction and properties of image deblurring problems along wit...
AbstractWe describe a modification of the conjugate gradient method for the normal equations (CGNR) ...
Abstract We consider Tikhonov regularization of large linear discrete ill-posed problems with a reg...
Abstract. Several numerical methods for the solution of large linear ill-posed problems combine Tikh...
Numerical solution of ill-posed problems is often accomplished by discretization (projection onto a...
The purpose of this thesis is to study how to overcome difficulties one typically encounters when so...
Abstract. We use the two-dimensional DCT to study several proper-ties of reconstructed images comput...
none3This paper introduces a new approach to computing an approximate solution of Tikhonov-regulariz...
Iterative Krylov subspace methods have proven to be efficient tools for solving linear systems of eq...
In this paper we present three theorems which give insight into the regularizing properties of MINRE...
The aim of this thesis is to study hybrid methods for solving ill-posed linear inverse problems corr...
Krylov subspace iterative methods have recently received considerable attention as regularizing tec...
Krylov subspace iterative methods have recently received considerable attention as regularizing tech...
In this thesis we consider a linear inverse problem Ax ≈ b with a smoothing operator A and a right-h...
The aim of this thesis is to study hybrid methods for solving ill-posed linear inverse problems corr...
The diploma thesis deals with the construction and properties of image deblurring problems along wit...
AbstractWe describe a modification of the conjugate gradient method for the normal equations (CGNR) ...
Abstract We consider Tikhonov regularization of large linear discrete ill-posed problems with a reg...
Abstract. Several numerical methods for the solution of large linear ill-posed problems combine Tikh...
Numerical solution of ill-posed problems is often accomplished by discretization (projection onto a...
The purpose of this thesis is to study how to overcome difficulties one typically encounters when so...
Abstract. We use the two-dimensional DCT to study several proper-ties of reconstructed images comput...
none3This paper introduces a new approach to computing an approximate solution of Tikhonov-regulariz...
Iterative Krylov subspace methods have proven to be efficient tools for solving linear systems of eq...
In this paper we present three theorems which give insight into the regularizing properties of MINRE...
The aim of this thesis is to study hybrid methods for solving ill-posed linear inverse problems corr...