Extended Krylov Subspaces: Approximation of the Matrix Square Root and Related Functions

We introduce an economical Gram--Schmidt orthogonalization on the extended Krylov subspace originated by actions of a symmetric matrix and its inverse. An error bound for a family of problems arising from the elliptic method of lines is derived. The bound shows that, for the same approximation quali...

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Bibliographic Details
Published in:SIAM journal on matrix analysis and applications 1998-07, Vol.19 (3), p.755
Main Authors: Druskin, Vladimir, Knizhnerman, Leonid
Format: Article
Language:English
Subjects:
Approximation
Control theory
Fourier transforms
Online Access:Get full text
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Summary:We introduce an economical Gram--Schmidt orthogonalization on the extended Krylov subspace originated by actions of a symmetric matrix and its inverse. An error bound for a family of problems arising from the elliptic method of lines is derived. The bound shows that, for the same approximation quality, the diagonal variant of the extended subspaces requires about the square root of the dimension of the standard Krylov subspaces using only positive or negative matrix powers. An example of an application to the solution of a 2.5-D elliptic problem attests to the computational efficiency of the method for large-scale problems.
ISSN:0895-4798
1095-7162
DOI:10.1137/S0895479895292400