A conjugate gradient projection method with restart procedure for solving constraint equations and image restorations

The conjugate gradient projection method is one of the most effective methods for solving large-scale nonlinear monotone convex constrained equations. In this paper, a new search direction with restart procedure is proposed, and a self-adjusting line search criterion is improved, then a three-term c...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of applied mathematics & computing Jg. 70; H. 3; S. 2255 - 2284
Hauptverfasser: Jiang, Xianzhen, Huang, Zefeng, Yang, Huihui
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2024
Springer Nature B.V
Schlagworte:
ISSN:1598-5865, 1865-2085
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The conjugate gradient projection method is one of the most effective methods for solving large-scale nonlinear monotone convex constrained equations. In this paper, a new search direction with restart procedure is proposed, and a self-adjusting line search criterion is improved, then a three-term conjugate gradient projection method is designed to solve the large-scale nonlinear monotone convex constrained equations and image restorations. Without using the Lipschitz continuity of these equations, the presented method is proved to be globally convergent. Moreover, its R-linear convergence rate is attained under Lipschitz continuity and the usual assumptions. Finally, large-scale numerical experiments for the convex constraint equations and image restorations have been performed, which show that the new method is effective.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1598-5865
1865-2085
DOI:10.1007/s12190-024-02044-0