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Three Results on Iterative Regularization

dc.contributor.authorKilmer, Mishaen_US
dc.contributor.authorStewart, G. W.en_US
dc.date.accessioned2004-05-31T22:53:58Z
dc.date.available2004-05-31T22:53:58Z
dc.date.created1998-10en_US
dc.date.issued1998-11-03en_US
dc.identifier.urihttp://hdl.handle.net/1903/975
dc.description.abstractIn this paper we present three theorems which give insight into the regularizing properties of {\minres}. While our theory does not completely characterize the regularizing behavior of the algorithm, it provides a partial explanation of the observed behavior of the method. Unlike traditional attempts to explain the regularizing properties of Krylov subspace methods, our approach focuses on convergence properties of the residual rather than on convergence analysis of the harmonic Ritz values. The import of our analysis is illustrated by two examples. In particular, our theoretical and numerical results support the following important observation: in some circumstances the dimension of the optimal Krylov subspace can be much smaller than the number of the components of the truncated spectral solution that must be computed to attain comparable accuracy. Also cross-referenced as UMIACS-TR-98-62en_US
dc.format.extent273914 bytes
dc.format.mimetypeapplication/postscript
dc.language.isoen_US
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-3949en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-98-62en_US
dc.titleThree Results on Iterative Regularizationen_US
dc.typeTechnical Reporten_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


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