Q-Curve and Area Rules for Choosing Heuristic Parameter in Tikhonov Regularization

Q-Curve and Area Rules for Choosing Heuristic Parameter in Tikhonov Regularization

We consider choice of the regularization parameter in Tikhonov method if the noise level of the data is unknown. One of the best rules for the heuristic parameter choice is the quasi-optimality criterion where the parameter is chosen as the global minimizer of the quasi-optimality function. In some...

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Bibliographic Details
Main Authors: Toomas Raus, Uno Hämarik
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Mathematics
Subjects:
ill-posed problem
Tikhonov regularization
unknown noise level
regularization parameter choice
heuristic rule
quasi-optimality function
Online Access:https://www.mdpi.com/2227-7390/8/7/1166

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https://www.mdpi.com/2227-7390/8/7/1166

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