Conjugate Gradients and Related KMP Algorithms: The Beginnings

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dc.contributor.authorO'Leary, Dianne P.en_US
dc.date.accessioned2004-05-31T22:35:35Z
dc.date.available2004-05-31T22:35:35Z
dc.date.created1995-11en_US
dc.date.issued1998-10-15en_US
dc.description.abstractIn the late 1940's and early 1950's, newly available computing machines generated intense interest in solving ``large'' systems of linear equations. Among the algorithms developed were several related methods, all of which generated bases for Krylov subspaces and used the bases to minimize or orthogonally project a measure of error. These methods include the conjugate gradient algorithm and the Lanczos algorithm. We refer to these algorithms as the KMP family and discuss its origins, emphasizing research themes that continue to have central importance. (Also cross-referenced as UMIACS-TR-95-107)en_US
dc.format.extent149813 bytes
dc.format.mimetypeapplication/postscript
dc.identifier.urihttp://hdl.handle.net/1903/771
dc.language.isoen_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-3556en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-95-107en_US
dc.titleConjugate Gradients and Related KMP Algorithms: The Beginningsen_US
dc.typeTechnical Reporten_US

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