A derivative-free three-term Hestenes-Stiefel type method for constrained nonlinear equations and image restoration

In this paper, a derivative-free Hestenes-Stielfel type method is proposed to solve large-scale nonlinear equations with convex constraints. The proposed method adopts the line search proposed by Ou and Li [J. Comput. Appl. Math. 56(1-2) (2018), pp. 195-216]. Unlike most existing methods, the global...

Full description

Saved in:
Bibliographic Details
Published inInternational journal of computer mathematics Vol. 99; no. 5; pp. 1041 - 1065
Main Authors Hassan Ibrahim, Abdulkarim, Kumam, Poom, Hassan, Basim A., Bala Abubakar, Auwal, Abubakar, Jamilu
Format Journal Article
LanguageEnglish
Published Abingdon Taylor & Francis 04.05.2022
Taylor & Francis Ltd
Subjects
compressive sensing
conjugate gradient method
Constraints
derivative-free method
Image restoration
Mathematical analysis
Nonlinear equations
projection method
Unconstrained optimization
Online AccessGet full text

Cover

More Information
Summary:In this paper, a derivative-free Hestenes-Stielfel type method is proposed to solve large-scale nonlinear equations with convex constraints. The proposed method adopts the line search proposed by Ou and Li [J. Comput. Appl. Math. 56(1-2) (2018), pp. 195-216]. Unlike most existing methods, the global convergence of the proposed method is established under the assumption that the underlying mapping is Lipschitz continuous and satisfies a weaker monotonicity condition. Preliminary numerical experiments indicate that the proposed method is effective and promising. Furthermore, the proposed method is used to solve image restoration problem in compressive sensing.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0020-7160
1029-0265
DOI:10.1080/00207160.2021.1946043