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Further convergence results on the general iteratively regularized Gauss-Newton methods under the discrepancy principle

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dc.contributor.authorJin, Qinian
dc.date.accessioned2016-03-11T05:47:50Z
dc.date.available2016-03-11T05:47:50Z
dc.date.issued2012-12-31
dc.date.updated2016-06-14T08:36:23Z
dc.description.abstractWe consider the general iteratively regularized Gauss-Newton methods for solving nonlinear inverse problems F(x) = y using the only available noise yδ satisfying||y δ -y|| ≤ δ with a given small noise level δ > 0. In order to produce reasonable approxi
dc.identifier.issn0025-5718en_AU
dc.identifier.urihttp://hdl.handle.net/1885/100232
dc.publisherAmerican Mathematical Society
dc.rights© 2012 American Mathematical Society
dc.sourceMathematics of Computation
dc.subjectNonlinear inverse problems
dc.subjectthe general iteratively regularized GaussNewton methods
dc.subjectthe discrepancy principle
dc.subjectconvergence
dc.subjectorder optimality
dc.titleFurther convergence results on the general iteratively regularized Gauss-Newton methods under the discrepancy principle
dc.typeJournal article
local.bibliographicCitation.issue283en_AU
local.bibliographicCitation.lastpage1665en_AU
local.bibliographicCitation.startpage1647en_AU
local.contributor.affiliationJin, Qinian, College of Physical and Mathematical Sciences, CPMS Mathematical Sciences Institute, Department of Mathematics, The Australian National Universityen_AU
local.contributor.authoruidu5085802en_AU
local.description.notesImported from ARIESen_AU
local.identifier.absfor010301en_AU
local.identifier.absseo970101en_AU
local.identifier.ariespublicationf5625xPUB4133en_AU
local.identifier.citationvolume82en_AU
local.identifier.doi10.1090/S0025-5718-2012-02665-2en_AU
local.identifier.scopusID2-s2.0-84878317202
local.publisher.urlhttp://www.ams.org/journals/en_AU
local.type.statusPublished Versionen_AU

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