AbstractIn this contribution a variation of Golub/Hansen/O’Leary’s Total Least-Squares (TLS) regularization technique is introduced, based on the Hybrid APproximation Solution (HAPS) within a nonlinear Gauss–Helmert Model. By applying a traditional Lagrange approach to a series of iteratively linearized Gauss–Helmert Models, a new iterative scheme has been found that, in practice, can generate the Tykhonov regularized TLS solution, provided that some care is taken to do the updates properly.The algorithm actually parallels the standard TLS approach as recommended in some of the geodetic literature, but unfortunately all too often in combination with erroneous updates that would still show convergence, although not necessarily to the (unregu...
This is a collection of information about regularized least squares (RLS). The facts here are not ne...
Tikhonov regularization is a powerful tool for the solution of ill-posed linear systems and linear l...
In a recent paper an algorithm for large-scale Tikhonov regularization in standard form called GKB-F...
AbstractIn this contribution a variation of Golub/Hansen/O’Leary’s Total Least-Squares (TLS) regular...
AbstractThe total least squares (TLS) method is a successful approach for linear problems when not o...
Discretizations of inverse problems lead to systems of linear equations with a highly ill-condition...
Discretizations of inverse problems lead to systems of linear equations with a highly ill-conditione...
. Discretizations of inverse problems lead to systems of linear equations with a highly ill-conditio...
The total least squares (TLS) method is a successful approach for linear problems if both the system...
AbstractIn this work, we study and analyze the regularized weighted total least squares (RWTLS) form...
The total least squares (TLS) method is a successful approach for linear problems if both the right-...
This thesis gives a brief introduction to Total Least Squares (TLS) comparing with the classical LS,...
The total least squares (TLS) method is a successful approach for linear problems if both the matrix...
In the first part of the thesis we review basic knowledge of regularized least squares problems and ...
Corrected version: caption for fig. 6.4, 6.5 and 6.6. (originally: ''orthogonal distances'', correct...
This is a collection of information about regularized least squares (RLS). The facts here are not ne...
Tikhonov regularization is a powerful tool for the solution of ill-posed linear systems and linear l...
In a recent paper an algorithm for large-scale Tikhonov regularization in standard form called GKB-F...
AbstractIn this contribution a variation of Golub/Hansen/O’Leary’s Total Least-Squares (TLS) regular...
AbstractThe total least squares (TLS) method is a successful approach for linear problems when not o...
Discretizations of inverse problems lead to systems of linear equations with a highly ill-condition...
Discretizations of inverse problems lead to systems of linear equations with a highly ill-conditione...
. Discretizations of inverse problems lead to systems of linear equations with a highly ill-conditio...
The total least squares (TLS) method is a successful approach for linear problems if both the system...
AbstractIn this work, we study and analyze the regularized weighted total least squares (RWTLS) form...
The total least squares (TLS) method is a successful approach for linear problems if both the right-...
This thesis gives a brief introduction to Total Least Squares (TLS) comparing with the classical LS,...
The total least squares (TLS) method is a successful approach for linear problems if both the matrix...
In the first part of the thesis we review basic knowledge of regularized least squares problems and ...
Corrected version: caption for fig. 6.4, 6.5 and 6.6. (originally: ''orthogonal distances'', correct...
This is a collection of information about regularized least squares (RLS). The facts here are not ne...
Tikhonov regularization is a powerful tool for the solution of ill-posed linear systems and linear l...
In a recent paper an algorithm for large-scale Tikhonov regularization in standard form called GKB-F...