We consider linear ill‐posed problems in Hilbert spaces with noisy right hand side and given noise level. For approximation of the solution the Tikhonov method or the iterated variant of this method may be used. In self‐adjoint problems the Lavrentiev method or its iterated variant are used. For a posteriori choice of the regularization parameter often quasioptimal rules are used which require computing of additionally iterated approximations. In this paper we propose for parameter choice alternative numerical schemes, using instead of additional iterations linear combinations of approximations with different parameters. First published online: 14 Oct 201
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do...
For the solution of linear ill-posed problems, in this paper we introduce a simple algorithm for the...
Regularization procedure involves the regularization parameter that plays a crucial role in the conv...
AbstractWe consider Tikhonov regularization of linear ill-posed problems with noisy data. The choice...
The paper considers posteriori strategies far choosing a parameter in a simplified in a simplified v...
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...
The well-known approach to solve the ill-posed problem is Tikhonov regularization scheme. But, the a...
Recently, Vasin and George (2013) considered an iterative scheme for approximately solving an ill-po...
We present a discrepancy-based parameter choice and stopping rule for iterative algorithms performin...
In the framework of iterative regularization techniques for large-scale linear ill-posed problems, t...
Tikhonov regularization is one of the most popular approaches to solve discrete ill-posed problems w...
In the framework of iterative regularization techniques for large-scale linear ill-posed problems, t...
Tikhonov regularization is one of the most popular approaches to solving linear discrete ill-posed p...
Tikhonov regularization is a popular method to approximate solutions of linear discrete ill-posed pr...
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do...
For the solution of linear ill-posed problems, in this paper we introduce a simple algorithm for the...
Regularization procedure involves the regularization parameter that plays a crucial role in the conv...
AbstractWe consider Tikhonov regularization of linear ill-posed problems with noisy data. The choice...
The paper considers posteriori strategies far choosing a parameter in a simplified in a simplified v...
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...
The well-known approach to solve the ill-posed problem is Tikhonov regularization scheme. But, the a...
Recently, Vasin and George (2013) considered an iterative scheme for approximately solving an ill-po...
We present a discrepancy-based parameter choice and stopping rule for iterative algorithms performin...
In the framework of iterative regularization techniques for large-scale linear ill-posed problems, t...
Tikhonov regularization is one of the most popular approaches to solve discrete ill-posed problems w...
In the framework of iterative regularization techniques for large-scale linear ill-posed problems, t...
Tikhonov regularization is one of the most popular approaches to solving linear discrete ill-posed p...
Tikhonov regularization is a popular method to approximate solutions of linear discrete ill-posed pr...
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do...
For the solution of linear ill-posed problems, in this paper we introduce a simple algorithm for the...
Regularization procedure involves the regularization parameter that plays a crucial role in the conv...