A sequential subspace projection method for linear symmetric eigenvalue problem (Q2846482)
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scientific article; zbMATH DE number 6206126
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | A sequential subspace projection method for linear symmetric eigenvalue problem |
scientific article; zbMATH DE number 6206126 |
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5 September 2013
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symmetric eigenvalue problem
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subspace projection
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Rayleigh quotient
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global convergence
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local convergence rate
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algorithm
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maximum eigenvalue
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eigenvector
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symmetric positive definite matrix
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numerical example
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A sequential subspace projection method for linear symmetric eigenvalue problem (English)
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The authors propose two sequential subspace projection algorithms for computing the maximum eigenvalue and the corresponding eigenvector of a symmetric positive definite matrix \(A\). They show that the algorithms (which utilize the relationship of this eigenvalue to the length of the shortest major axis of the ellipsoid \(x^TAx=1\)) are globally convergent, and find their rate of local linear convergence, as well as comparing their performance on some numerical examples with that of the MATLAB solver EIGS.
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