Solving or resolving inadequate and noisy tomographic systems

DOI10.1016/0021-9991(85)90075-0zbMath0589.65086OpenAlexW2086784326MaRDI QIDQ1074329

Guust Nolet

Publication date: 1985

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://dspace.library.uu.nl/handle/1874/16491

zbMATH Keywords

noisy dataRadon transformsingular value decompositionill-posed problemtomographyinversionconjugate gradientsLandweber iterationseismologystabilization methodsDines-Lytle methodregularisation by iterative methods

Mathematics Subject Classification ID

Seismology (including tsunami modeling), earthquakes (86A15) Special integral transforms (Legendre, Hilbert, etc.) (44A15) Iterative numerical methods for linear systems (65F10) Numerical methods for integral transforms (65R10)

Related Items (5)

Fast \(l_ p\) solution of large, sparse, linear systems: Application to seismic travel time tomography ⋮ ON TIKHONOV REGULARIZATION AND COMPRESSIVE SENSING FOR SEISMIC SIGNAL PROCESSING ⋮ Preconditioning non-monotone gradient methods for retrieval of seismic reflection signals ⋮ Regularization properties of LSQR for linear discrete ill-posed problems in the multiple singular value case and best, near best and general low rank approximations ⋮ SIRT- and CG-type methods for the iterative solution of sparse linear least-squares problems

Uses Software

• LSQR

Cites Work

• LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
• Accelerated projection methods for computing pseudoinverse solutions of systems of linear equations
• Calculating the Singular Values and Pseudo-Inverse of a Matrix
• Unnamed Item

This page was built for publication: Solving or resolving inadequate and noisy tomographic systems