Convergence of algorithms for finding eigenvectors (Q1594858)
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scientific article; zbMATH DE number 1558284
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Convergence of algorithms for finding eigenvectors |
scientific article; zbMATH DE number 1558284 |
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Convergence of algorithms for finding eigenvectors (English)
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29 January 2001
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A new iteration algorithm is introduced for solving symmetric matrix eigenvalue problems. The method is a generalization of the stochastic gradient ascent method used for principal component analysis in pattern recognition. The convergence of the algorithm is proved and numerical examples are presented.
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eigenvectors
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iteration algorithm
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symmetric matrix eigenvalue problems
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stochastic gradient ascent method
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principal component analysis
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pattern recognition
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convergence
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numerical examples
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0.9087497
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0.8949435
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0.89414954
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0.8928944
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0.8888918
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