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On Estimating the Condition of Eigenvalues and Eigenvectors

dc.contributor.authorVan Loan, Charlesen_US
dc.date.accessioned2007-04-23T17:12:33Z
dc.date.available2007-04-23T17:12:33Z
dc.date.issued1986-01en_US
dc.description.abstractA method is developed for estimating the accuracy of computed eigenvalues and eigenvectors that are obtained via certain EISPACK subroutines. It does this at a cost of $O(n^{2})$ flops per eigenpair assuming that the eigenpair is known and assuming that the original matrix has been reduced to Hessenberg form. The heart of the technique involves estimating the smallest singular value of a certain nearly triangular submatrix. This is accomplished by some standard "zero-chasing" with Hivens transformations and with a 2-norm version of the LINPACK condition estimator. An EISPACK compatible code has been developed and its performance is discussed. Suggestions for extending the current work to general invariant subspaces and to the generalized eigenvalue problem are given.en_US
dc.format.extent1797286 bytes
dc.format.extent405883 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.identifier.citationhttp://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR86-726en_US
dc.identifier.urihttps://hdl.handle.net/1813/6566
dc.language.isoen_USen_US
dc.publisherCornell Universityen_US
dc.subjectcomputer scienceen_US
dc.subjecttechnical reporten_US
dc.titleOn Estimating the Condition of Eigenvalues and Eigenvectorsen_US
dc.typetechnical reporten_US

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