Accelerating the Lanczos Algorithm via Polynomial Spectral Transformations

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dc.contributor.authorSorensen, D.C.en_US
dc.contributor.authorYang, C.en_US
dc.date.accessioned2018-06-18T17:44:06Zen_US
dc.date.available2018-06-18T17:44:06Zen_US
dc.date.issued1997-11en_US
dc.date.noteNovember 1997en_US
dc.description.abstractWe consider the problem of computing a few clustered and/or interior eigenvalues of a symmetric matrix A without using a matrix factorization. This can be done by applying the Lanczos algorithm to p(A), where p(lambda) is a polynomial that maps the clustered and/or interior eigenvalues of A to extremal and well separated eigenvalues of p(A). We will demonstrate and compare several techniques of constructing these polynomials. Numerical examples are presented to illustrate the effectiveness of using these polynomial to accelerate the Lanczos process.en_US
dc.format.extent25 ppen_US
dc.identifier.citationSorensen, D.C. and Yang, C.. "Accelerating the Lanczos Algorithm via Polynomial Spectral Transformations." (1997) <a href="https://hdl.handle.net/1911/101895">https://hdl.handle.net/1911/101895</a>.en_US
dc.identifier.digitalTR97-29en_US
dc.identifier.urihttps://hdl.handle.net/1911/101895en_US
dc.language.isoengen_US
dc.titleAccelerating the Lanczos Algorithm via Polynomial Spectral Transformationsen_US
dc.typeTechnical reporten_US
dc.type.dcmiTexten_US
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