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Krylov subspace solvers and preconditioners. (English) Zbl 1406.65021
The author offers a special point of view to the subject of numerical solution of systems of linear equations (SLE), with particular emphasis on the Krylov subspace method for the SLE with a symmetric positive definite matrix. The conjugate gradient method is studied in detail and good upper bounds of the distance between \(k\)-th iterate and the exact solution of the SLE are obtained. Good examples to illustrate a super-linear convergence behavior are provided. Analogous questions for the SLE with the “preconditioner” matrix and with a “general” matrix are considered. The investigations are of interest to the following topics: solving large, sparse systems of linear equations.
MSC:
65F10 Iterative numerical methods for linear systems
65F08 Preconditioners for iterative methods
65F50 Computational methods for sparse matrices
Software:
LSQR; CGS
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References:
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