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Article . 2024 . Peer-reviewed
License: CC BY
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Modelling
Article . 2024 . Peer-reviewed
License: CC BY
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Modelling
Article . 2024
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Parameter Choice Strategy That Computes Regularization Parameter before Computing the Regularized Solution

Authors: Santhosh George; Jidesh Padikkal; Ajil Kunnarath; Ioannis K. Argyros; Samundra Regmi;

Parameter Choice Strategy That Computes Regularization Parameter before Computing the Regularized Solution

Abstract

The modeling of many problems of practical interest leads to nonlinear ill-posed equations (for example, the parameter identification problem (see the Numerical section)). In this article, we introduce a new source condition (SC) and a new parameter choice strategy (PCS) for the Tikhonov regularization (TR) method for nonlinear ill-posed problems. The new PCS is introduced using a new SC to compute the regularization parameter (RP) before computing the regularized solution. The theoretical results are verified using a numerical example.

Keywords

ill-posed problems, parameter choice strategy, Engineering design, TA174, source condition, Tikhonov regularization method

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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