Show simple item record

Well-Posedness and Convergence of Some Regularization Methods for Nonlinear Ill-Posed Problems.

dc.contributor.authorSeidman, T.I.en_US
dc.contributor.authorVogel, C.R.en_US
dc.date.accessioned2007-05-23T09:37:52Z
dc.date.available2007-05-23T09:37:52Z
dc.date.issued1987en_US
dc.identifier.urihttp://hdl.handle.net/1903/4604
dc.description.abstractIn this paper we analyze two regularization methods for nonlinear ill-posed problems. The first is a penalty method called Tikhonov regularization, in which one solves an unconstrained optimization problem while the second is based on a constrained optimization problem. For each method we examine the well- posedness of the respective optimization problem. We then show strong convergence of the regularized 'solutions' to the true solution. (Note that this is well known for the application of these methods to linear problems.) In this analysis we consider such factors as the convergence of perturbed data to the true data, inexact solution of the respective optimization problems, and the choice of the regularization parameters.en_US
dc.format.extent702577 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1987-96en_US
dc.titleWell-Posedness and Convergence of Some Regularization Methods for Nonlinear Ill-Posed Problems.en_US
dc.typeTechnical Reporten_US
dc.contributor.departmentISRen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record