Tomography in seismology often leads to underdetermined and inconsistent systems of linear equations. When solving, care must be taken to keep the propagation of data errors under control. In this paper I test the applicability of three types of damped least-squares algorithms to the kind of sparse matrices encountered in seismic tomography: (1) singular value decomposition with Lanczos iteration, (2) conjugate gradient iteration with the LSQR algorithm, and (3) the Dines-Lytle method. Lanczos iteration may be applied to large sparse systems of low rank to calculate solutions by singular value decomposition but becomes impractical with problems of larger size. The Paige-Saunders algorithm (LSQR), which incorporates Lanczos' iteration ...
We propose a greedy inversion method for sparse linear problems. The kernel of the method is based o...
International audienceWe present a realistic application of an inversion scheme for global seismic t...
A problem frequently encountered in the earth sciences requires deducing physical parameters of the ...
International audienceWe present a new approach to reduce a sparse, linear system of equations assoc...
This research investigates iterative methods for solving large and sparse least squares problems, as...
Inverse problems Parallel scientific computing a b s t r a c t The LSQR algorithm developed by Paige...
A fast technological progress is providing seismic tomographers with computers of rapidly increasin...
AbstractSIRT and CG-type methods have been successfully employed for the approximate solution of lea...
The effects of several nonlinear regularization techniques are discussed in the framework of 3D seis...
Seismic tomography inverse problems are among the largest high-dimensional parameter estimation task...
Methods are developed for design of linear tomographic reconstruction algorithms with specified prop...
AbstractLeast Squares with QR-factorization (LSQR) method is a widely used Krylov subspace algorithm...
This thesis will address the large computational costs of solving least-squares migration and full-w...
International audienceThe appraisal of tomographic models, of fundamental importance towards better ...
We present a realistic application of an inversion scheme for global seismic tomography that uses as...
We propose a greedy inversion method for sparse linear problems. The kernel of the method is based o...
International audienceWe present a realistic application of an inversion scheme for global seismic t...
A problem frequently encountered in the earth sciences requires deducing physical parameters of the ...
International audienceWe present a new approach to reduce a sparse, linear system of equations assoc...
This research investigates iterative methods for solving large and sparse least squares problems, as...
Inverse problems Parallel scientific computing a b s t r a c t The LSQR algorithm developed by Paige...
A fast technological progress is providing seismic tomographers with computers of rapidly increasin...
AbstractSIRT and CG-type methods have been successfully employed for the approximate solution of lea...
The effects of several nonlinear regularization techniques are discussed in the framework of 3D seis...
Seismic tomography inverse problems are among the largest high-dimensional parameter estimation task...
Methods are developed for design of linear tomographic reconstruction algorithms with specified prop...
AbstractLeast Squares with QR-factorization (LSQR) method is a widely used Krylov subspace algorithm...
This thesis will address the large computational costs of solving least-squares migration and full-w...
International audienceThe appraisal of tomographic models, of fundamental importance towards better ...
We present a realistic application of an inversion scheme for global seismic tomography that uses as...
We propose a greedy inversion method for sparse linear problems. The kernel of the method is based o...
International audienceWe present a realistic application of an inversion scheme for global seismic t...
A problem frequently encountered in the earth sciences requires deducing physical parameters of the ...