Analysis of approximate inverses in tomography. II: Iterative inverses
DOI10.1023/A:1011588308111zbMath1014.65138OpenAlexW1522044076MaRDI QIDQ1863847
Publication date: 12 March 2003
Published in: Optimization and Engineering (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1023/a:1011588308111
numerical methodssingular-value decompositionsingular valueacoustic tomographyapproximate inversesreorthogonalizationresolution matricesconjugate gradients decompositioniterative inverses
Biomedical imaging and signal processing (92C55) Seismology (including tsunami modeling), earthquakes (86A15) Radon transform (44A12) Numerical methods for integral transforms (65R10)
Cites Work
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- Computing projections with LSQR
- SIRT- and CG-type methods for the iterative solution of sparse linear least-squares problems
- Analysis of approximate inverses in tomography. I: Resolution analysis of common inverses
- The best generalized inverse
- Solution of sparse rectangular systems using LSQR and Craig
- A Taxonomy for Conjugate Gradient Methods
- Stable iterative reconstruction algorithm for nonlinear traveltime tomography
- LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
- Predicting the Behavior of Finite Precision Lanczos and Conjugate Gradient Computations
- Accelerated projection methods for computing pseudoinverse solutions of systems of linear equations
- Function minimization by conjugate gradients
- Calculating the Singular Values and Pseudo-Inverse of a Matrix
- The principle of minimized iterations in the solution of the matrix eigenvalue problem
- Methods of conjugate gradients for solving linear systems
- The N‐Step Iteration Procedures
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