AbstractDiscretization of linear inverse problems generally gives rise to very ill-conditioned linear systems of algebraic equations. Typically, the linear systems obtained have to be regularized to make the computation of a meaningful approximate solution possible. Tikhonov regularization is one of the most popular regularization methods. A regularization parameter specifies the amount of regularization and, in general, an appropriate value of this parameter is not known a priori. We review available iterative methods, and present new ones, for the determination of a suitable value of the regularization parameter by the L-curve criterion and the solution of regularized systems of algebraic equations
Tikhonov regularization is a powerful tool for the solution of ill-posed linear systems and linear l...
University of Minnesota Ph.D. dissertation. March 2011. Advisor:Prof. Fadil Santosa. Major: Mathemat...
A Generalized Tikhonov Regularization Using Two Parameters Applied to Linear Inverse Ill-Posed Probl...
Discretization of linear inverse problems generally gives rise to very ill-conditioned linear system...
AbstractIn this paper we introduce a new variant of L-curve to estimate the Tikhonov regularization ...
In a Tikhonov regularization scheme to solve discrete linear ill-posed problems, selecting the param...
Abstract. Straightforward solution of discrete ill-posed linear systems of equations or least-square...
This paper presents a method for choosing the regular-ization parameter (α) appearing in Tikhonov re...
Straightforward solution of discrete ill-posed linear systems of equations or least-squares problems...
In this paper, we propose a new strategy for a priori choice of reg-ularization parameters in Tikhon...
This paper introduces a new strategy for setting the regularization parameter when solving large-sca...
. Discretizations of inverse problems lead to systems of linear equations with a highly ill-conditio...
In a Tikhonov regularization scheme to solve discrete linear ill-posed problems, selecting the param...
AbstractWe propose a method for choosing the regularization parameter in iterated Tikhonov regulariz...
Ill-posed inverse problems arise in many fields of science and engineering. The ill-conditioning and...
Tikhonov regularization is a powerful tool for the solution of ill-posed linear systems and linear l...
University of Minnesota Ph.D. dissertation. March 2011. Advisor:Prof. Fadil Santosa. Major: Mathemat...
A Generalized Tikhonov Regularization Using Two Parameters Applied to Linear Inverse Ill-Posed Probl...
Discretization of linear inverse problems generally gives rise to very ill-conditioned linear system...
AbstractIn this paper we introduce a new variant of L-curve to estimate the Tikhonov regularization ...
In a Tikhonov regularization scheme to solve discrete linear ill-posed problems, selecting the param...
Abstract. Straightforward solution of discrete ill-posed linear systems of equations or least-square...
This paper presents a method for choosing the regular-ization parameter (α) appearing in Tikhonov re...
Straightforward solution of discrete ill-posed linear systems of equations or least-squares problems...
In this paper, we propose a new strategy for a priori choice of reg-ularization parameters in Tikhon...
This paper introduces a new strategy for setting the regularization parameter when solving large-sca...
. Discretizations of inverse problems lead to systems of linear equations with a highly ill-conditio...
In a Tikhonov regularization scheme to solve discrete linear ill-posed problems, selecting the param...
AbstractWe propose a method for choosing the regularization parameter in iterated Tikhonov regulariz...
Ill-posed inverse problems arise in many fields of science and engineering. The ill-conditioning and...
Tikhonov regularization is a powerful tool for the solution of ill-posed linear systems and linear l...
University of Minnesota Ph.D. dissertation. March 2011. Advisor:Prof. Fadil Santosa. Major: Mathemat...
A Generalized Tikhonov Regularization Using Two Parameters Applied to Linear Inverse Ill-Posed Probl...