Add to ORKGChoosing the regularization parameter for an ill-posed problem is an art based on good heuristics and prior knowledge of the noise in the observations. In this work we propose choosing the parameter, without a priori information, by approximately minimizing the distance between the true solution to the discrete problem and the family of regularized solutions. We demonstrate the usefulness of this approach for Tikhonov regularization and for an alternate family of solutions. Further, we prove convergence of the regularization parameter to zero as the standard deviation of the noise goes to zero. We also prove that the alternate family produces solutions closer to the true solution than the Tikhonov family when the noise is small enough. Al...
This paper is concerned with the solution of large-scale linear discrete ill-posed problems with err...
summary:We give a derivation of an a-posteriori strategy for choosing the regularization parameter i...
summary:We give a derivation of an a-posteriori strategy for choosing the regularization parameter i...
AbstractWe consider Tikhonov regularization of linear ill-posed problems with noisy data. The choice...
The straightforward solution of discrete ill-posed linear systems of equations or least-squares prob...
The straightforward solution of discrete ill-posed linear systems of equations or least-squares prob...
Multiplicative regularization solves a linear inverse problem by minimizing the product of the norm ...
AbstractIn this paper we introduce a new variant of L-curve to estimate the Tikhonov regularization ...
The straightforward solution of discrete ill-posed linear systems of equations or least-squares prob...
Straightforward solution of discrete ill-posed linear systems of equations or least-squares problems...
Multiplicative regularization solves a linear inverse problem by minimizing the product of the norm ...
The paper considers posteriori strategies far choosing a parameter in a simplified in a simplified v...
The straightforward solution of discrete ill-posed linear systems of equations or least-squares prob...
The straightforward solution of discrete ill-posed linear systems of equations or least-squares prob...
Straightforward solution of discrete ill-posed linear systems of equations or least-squares problems...
This paper is concerned with the solution of large-scale linear discrete ill-posed problems with err...
summary:We give a derivation of an a-posteriori strategy for choosing the regularization parameter i...
summary:We give a derivation of an a-posteriori strategy for choosing the regularization parameter i...
AbstractWe consider Tikhonov regularization of linear ill-posed problems with noisy data. The choice...
The straightforward solution of discrete ill-posed linear systems of equations or least-squares prob...
The straightforward solution of discrete ill-posed linear systems of equations or least-squares prob...
Multiplicative regularization solves a linear inverse problem by minimizing the product of the norm ...
AbstractIn this paper we introduce a new variant of L-curve to estimate the Tikhonov regularization ...
The straightforward solution of discrete ill-posed linear systems of equations or least-squares prob...
Straightforward solution of discrete ill-posed linear systems of equations or least-squares problems...
Multiplicative regularization solves a linear inverse problem by minimizing the product of the norm ...
The paper considers posteriori strategies far choosing a parameter in a simplified in a simplified v...
The straightforward solution of discrete ill-posed linear systems of equations or least-squares prob...
The straightforward solution of discrete ill-posed linear systems of equations or least-squares prob...
Straightforward solution of discrete ill-posed linear systems of equations or least-squares problems...
This paper is concerned with the solution of large-scale linear discrete ill-posed problems with err...
summary:We give a derivation of an a-posteriori strategy for choosing the regularization parameter i...
summary:We give a derivation of an a-posteriori strategy for choosing the regularization parameter i...