For solving linear ill-posed problems, regularization methods are required when the right-hand side is with some noise. In this paper regularized solutions are obtained by implicit iteration methods in Hilbert scales. By exploiting operator monotonicity of certain functions and interpolation techniques in variable Hilbert scales, we study these methods under general smoothness conditions. Order optimal error bounds are given in case the regularization parameter is chosen either a priori or a posteriori by the discrepancy principle. For realizing the discrepancy principle, some fast algorithm is proposed which is based on Newton's method applied to some properly transformed equations
We study the efficiency of the approximate solution of ill-posed problems, based on discretized obse...
A class of regularization methods using unbounded regularizing operators is considered for obtaining...
In the analysis of ill-posed inverse problems the impact of solution smoothness on accuracy and conv...
For solving linear ill-posed problems with noisy data, regularization methods are required. In the p...
Simplified regularization using finite-dimensional approximations in the setting of Hilbert scales h...
Inexact Newton regularization methods have been proposed by Hanke and Rieder for solving nonlinear i...
We consider a class of inexact Newton regularization methods for solving nonlinear inverse problems ...
Recently, Tautenhahn and Hämarik (1999) have considered a monotone rule as a parameter choice strate...
Recently, Vasin and George (2013) considered an iterative scheme for approximately solving an ill-po...
We study the efficiency of the approximate solution of ill-posed problems, based on discretized nois...
In this paper we investigate convergence of Landweber iteration in Hilbert scales for linear and non...
A new version of the simple iterations implicit method based on the singular value decomposition is ...
Based on the variable Hilbert scale interpolation inequality, bounds for the error of regularisation...
In this paper we discuss a relation between Learning Theory and Regularization of linear ill-posed i...
AbstractWe consider the analysis of regularization problems in state space for nonlinear implicit op...
We study the efficiency of the approximate solution of ill-posed problems, based on discretized obse...
A class of regularization methods using unbounded regularizing operators is considered for obtaining...
In the analysis of ill-posed inverse problems the impact of solution smoothness on accuracy and conv...
For solving linear ill-posed problems with noisy data, regularization methods are required. In the p...
Simplified regularization using finite-dimensional approximations in the setting of Hilbert scales h...
Inexact Newton regularization methods have been proposed by Hanke and Rieder for solving nonlinear i...
We consider a class of inexact Newton regularization methods for solving nonlinear inverse problems ...
Recently, Tautenhahn and Hämarik (1999) have considered a monotone rule as a parameter choice strate...
Recently, Vasin and George (2013) considered an iterative scheme for approximately solving an ill-po...
We study the efficiency of the approximate solution of ill-posed problems, based on discretized nois...
In this paper we investigate convergence of Landweber iteration in Hilbert scales for linear and non...
A new version of the simple iterations implicit method based on the singular value decomposition is ...
Based on the variable Hilbert scale interpolation inequality, bounds for the error of regularisation...
In this paper we discuss a relation between Learning Theory and Regularization of linear ill-posed i...
AbstractWe consider the analysis of regularization problems in state space for nonlinear implicit op...
We study the efficiency of the approximate solution of ill-posed problems, based on discretized obse...
A class of regularization methods using unbounded regularizing operators is considered for obtaining...
In the analysis of ill-posed inverse problems the impact of solution smoothness on accuracy and conv...