On IOM(q): The Incomplete Orthogonalization Method for Large Unsymmetric Linear Systems
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Publication:4220444
DOI<491::AID-NLA87>3.0.CO;2-9 10.1002/(SICI)1099-1506(199611/12)3:6<491::AID-NLA87>3.0.CO;2-9zbMath0906.65034OpenAlexW2090067480MaRDI QIDQ4220444
Publication date: 23 November 1998
Full work available at URL: https://doi.org/10.1002/(sici)1099-1506(199611/12)3:6<491::aid-nla87>3.0.co;2-9
convergencenumerical examplesKrylov subspacesfull orthogonalization methodunsymmetric linear systemsincomplete orthogonalization methodIOM\((q)\)orthogonality of basis vectorsrestarted FOM method
Iterative numerical methods for linear systems (65F10) Orthogonalization in numerical linear algebra (65F25)
Related Items
Some recursions on Arnoldi's method and IOM for large non-Hermitian linear systems, On IGMRES: An incomplete generalized minimal residual method for large unsymmetric linear systems, The convergence of Krylov subspace methods for large unsymmetric linear systems
Cites Work
- Unnamed Item
- Necessary and sufficient conditions for the simplification of generalized conjugate-gradient algorithms
- A new look at the Lanczos algorithm for solving symmetric systems of linear equations
- Conjugate gradient type methods for unsymmetric and inconsistent systems of linear equations
- Variations on Arnoldi's method for computing eigenelements of large unsymmetric matrices
- Generalized conjugate-gradient acceleration of nonsymmetrizable iterative methods
- QMR: A quasi-minimal residual method for non-Hermitian linear systems
- An efficient nonsymmetric Lanczos method on parallel vector computers
- A block incomplete orthogonalization method for large nonsymmetric eigenproblems
- Variational Iterative Methods for Nonsymmetric Systems of Linear Equations
- Practical Use of Some Krylov Subspace Methods for Solving Indefinite and Nonsymmetric Linear Systems
- Iterative Solution of Linear Equations in ODE Codes
- Necessary and Sufficient Conditions for the Existence of a Conjugate Gradient Method
- Krylov Subspace Methods on Supercomputers
- Implementation of the GMRES Method Using Householder Transformations
- Hybrid Krylov Methods for Nonlinear Systems of Equations
- GMRES: A Generalized Minimal Residual Algorithm for Solving Nonsymmetric Linear Systems
- Some History of the Conjugate Gradient and Lanczos Algorithms: 1948–1976
- The Lanczos Biorthogonalization Algorithm and Other Oblique Projection Methods for Solving Large Unsymmetric Systems
- s-Step Iterative Methods for (Non)Symmetric (In)Definite Linear Systems
- Reduction to Tridiagonal Form and Minimal Realizations
- A Completed Theory of the Unsymmetric Lanczos Process and Related Algorithms, Part I
- A Hybrid GMRES Algorithm for Nonsymmetric Linear Systems
- Parallelizable restarted iterative methods for nonsymmetric linear systems. part I: Theory
- A Completed Theory of the Unsymmetric Lanczos Process and Related Algorithms. Part II
- A Robust GMRES-Based Adaptive Polynomial Preconditioning Algorithm for Nonsymmetric Linear Systems
- A Comparison of Preconditioned Nonsymmetric Krylov Methods on a Large-Scale MIMD Machine
- Orthogonal Error Methods
- GMRESR: a family of nested GMRES methods
- A Theoretical Comparison of the Arnoldi and GMRES Algorithms
- The principle of minimized iterations in the solution of the matrix eigenvalue problem
