Numerical approximation of a Tikhonov type regularizer by a discretized frozen steepest descent method

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dc.contributor.authorGeorge, S.
dc.contributor.authorSabari, M.
dc.date.accessioned2026-02-05T09:31:33Z
dc.date.issued2018
dc.description.abstractWe present a frozen regularized steepest descent method and its finite dimensional realization for obtaining an approximate solution for the nonlinear ill-posed operator equation F(x)=y. The proposed method is a modified form of the method considered by Argyros et al. (2014). The balancing principle considered by Pereverzev and Schock (2005) is used for choosing the regularization parameter. The error estimate is derived under a general source condition and is of optimal order. The provided numerical example proves the efficiency of the proposed method. © 2017 Elsevier B.V.
dc.identifier.citationJournal of Computational and Applied Mathematics, 2018, 330, , pp. 488-498
dc.identifier.issn3770427
dc.identifier.urihttps://doi.org/10.1016/j.cam.2017.09.022
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/25251
dc.publisherElsevier B.V.
dc.subjectMathematical operators
dc.subjectNonlinear equations
dc.subjectNumerical methods
dc.subjectApproximate solution
dc.subjectError estimates
dc.subjectFinite dimensional
dc.subjectIll-posed operator equation
dc.subjectNonlinear ill-posed problems
dc.subjectNumerical approximations
dc.subjectOptimal ordering
dc.subjectRegularization parameters
dc.subjectSteepest descent method
dc.titleNumerical approximation of a Tikhonov type regularizer by a discretized frozen steepest descent method

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