A sufficient descent LS-PRP-BFGS-like method for solving nonlinear monotone equations with application to image restoration

A. B. Abubakar, A. H. Ibrahim, M. Abdullahi, M. Aphane, Jiawei Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

In this paper, we propose a method for efficiently obtaining an approximate solution for constrained nonlinear monotone operator equations. The search direction of the proposed method closely aligns with the Broyden-Fletcher-Goldfarb-Shanno (BFGS) direction, known for its low storage requirement. Notably, the search direction is shown to be sufficiently descent and bounded without using the line search condition. Furthermore, under some standard assumptions, the proposed method converges globally. As an application, the proposed method is applied to solve image restoration problems. The efficiency and robustness of the method in comparison to other methods are tested by numerical experiments using some test problems.

Original languageEnglish
Pages (from-to)1423-1464
Number of pages42
JournalNumerical Algorithms
Volume96
Issue number4
DOIs
StatePublished - Aug 2024

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.

Keywords

  • 65K05
  • 90C52
  • 90C56
  • 94A08
  • Global convergence
  • Image restoration
  • Nonlinear equations
  • Projection map

ASJC Scopus subject areas

  • Applied Mathematics

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