Inexact Newton regularization methods have been proposed by Hanke and Rieder for solving nonlinear ill-posed inverse problems. Every such a method consists of two components: an outer Newton iteration and an inner scheme providing increments by regularizing local linearized equations. The method is terminated by a discrepancy principle. In this paper we consider the inexact Newton regularization methods with the inner scheme defined by Landweber iteration, the implicit iteration, the asymptotic regularization and Tikhonov regularization. Under certain conditions we obtain the order optimal convergence rate result which improves the suboptimal one of Rieder. We in fact obtain a more general order optimality result by considering these inexac...
When iterative methods are employed as regularizers of inverse problems, a main issue is the trade-o...
summary:We give a derivation of an a-posteriori strategy for choosing the regularization parameter i...
We study the efficiency of the approximate solution of ill-posed problems, based on discretized obse...
We consider a class of inexact Newton regularization methods for solving nonlinear inverse problems ...
Inverse problems arise whenever one searches for unknown causes based on observation of their effect...
In this paper we consider the iteratively regularized Gauss-Newton method for solving nonlinear ill-...
For solving linear ill-posed problems, regularization methods are required when the right-hand side ...
Recently, Vasin and George (2013) considered an iterative scheme for approximately solving an ill-po...
We consider a regularized Levenberg-Marquardt method for solving nonlinear ill-posed inverse problem...
We develop a general convergence analysis for a class of inexact Newton-type regularizations for sta...
This paper develops truncated Newton methods as an appropriate tool for nonlinear inverse problems w...
AbstractRecently, a new iterative method, called Newton–Lavrentiev regularization (NLR) method, was ...
Abstract. A classical model of Newton iterations which takes into account some error terms is given ...
A class of regularization methods using unbounded regularizing operators is considered for obtaining...
Abstract. The iteratively regularized Gauss-Newton method is applied to compute the stable solutions...
When iterative methods are employed as regularizers of inverse problems, a main issue is the trade-o...
summary:We give a derivation of an a-posteriori strategy for choosing the regularization parameter i...
We study the efficiency of the approximate solution of ill-posed problems, based on discretized obse...
We consider a class of inexact Newton regularization methods for solving nonlinear inverse problems ...
Inverse problems arise whenever one searches for unknown causes based on observation of their effect...
In this paper we consider the iteratively regularized Gauss-Newton method for solving nonlinear ill-...
For solving linear ill-posed problems, regularization methods are required when the right-hand side ...
Recently, Vasin and George (2013) considered an iterative scheme for approximately solving an ill-po...
We consider a regularized Levenberg-Marquardt method for solving nonlinear ill-posed inverse problem...
We develop a general convergence analysis for a class of inexact Newton-type regularizations for sta...
This paper develops truncated Newton methods as an appropriate tool for nonlinear inverse problems w...
AbstractRecently, a new iterative method, called Newton–Lavrentiev regularization (NLR) method, was ...
Abstract. A classical model of Newton iterations which takes into account some error terms is given ...
A class of regularization methods using unbounded regularizing operators is considered for obtaining...
Abstract. The iteratively regularized Gauss-Newton method is applied to compute the stable solutions...
When iterative methods are employed as regularizers of inverse problems, a main issue is the trade-o...
summary:We give a derivation of an a-posteriori strategy for choosing the regularization parameter i...
We study the efficiency of the approximate solution of ill-posed problems, based on discretized obse...