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A new variant of Arnoldi method for approximation of eigenpairs
Published in Elsevier B.V.
2018
Volume: 344
   
Pages: 424 - 437
Abstract
Arnoldi method approximates exterior eigenvalues of a large sparse matrix, but may fail to approximate corresponding eigenvectors. The refined Arnoldi method approximates an eigenpair by solving a related singular value problem. In this paper, we propose a new procedure to extract an approximate eigenpair from a Krylov subspace in Arnoldi method, using a minimization problem. Unlike the refined Arnoldi method, the suggested procedure requires solving a linear system. © 2018 Elsevier B.V.
About the journal
JournalData powered by TypesetJournal of Computational and Applied Mathematics
PublisherData powered by TypesetElsevier B.V.
ISSN03770427
Open AccessNo
Concepts (10)
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    Linear systems
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    ARNOLDI METHOD
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    Eigenvalues
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    EIGENVALUES AND EIGENVECTORS
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    KRYLOV SUB SPACES
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    LARGE SPARSE MATRIX
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    Minimization problems
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    REFINED ARNOLDI METHODS
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    Singular values
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    Eigenvalues and eigenfunctions