A new step size rule for the superiorization method and its application in computerized tomography

In this paper, we consider a regularized least squares problem subject to convex constraints. Our algorithm is based on the superiorization technique, equipped with a new step size rule which uses subgradient projections. The superiorization method is a two-step method where one step reduces the val...

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Veröffentlicht in:	Numerical algorithms Jg. 90; H. 3; S. 1253 - 1277
Hauptverfasser:	Nikazad, T., Abbasi, M., Afzalipour, L., Elfving, T.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.07.2022 Springer Nature B.V
Schlagworte:	Algebra Algorithms Computed tomography Computer Science Conjugate gradient method Convergence Iterative methods Least squares method Numeric Computing Numerical Analysis Original Paper Regularization Theory of Computation Tomography Strictly quasi-nonexpansive operator Convex feasibility problem Computed tomography 65F10 Convex optimization Sequential block method Perturbation resilient iterative method 47J25 Superiorization 47H14
ISSN:	1017-1398, 1572-9265, 1572-9265
Online-Zugang:	Volltext
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