An Algorithm That Adjusts the Stepsize to Be Self-Adaptive with an Inertial Term Aimed for Solving Split Variational Inclusion and Common Fixed Point Problems

Matlhatsi Dorah Ngwepe, Lateef Olakunle Jolaoso*, Maggie Aphane, Ibrahim Oyeyemi Adenekan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In this research paper, we present a new inertial method with a self-adaptive technique for solving the split variational inclusion and fixed point problems in real Hilbert spaces. The algorithm is designed to choose the optimal choice of the inertial term at every iteration, and the stepsize is defined self-adaptively without a prior estimate of the Lipschitz constant. A convergence theorem is demonstrated to be strong even under lenient conditions and to showcase the suggested method’s efficiency and precision. Some numerical tests are given. Moreover, the significance of the proposed method is demonstrated through its application to an image reconstruction issue.

Original languageEnglish
Article number4708
JournalMathematics
Volume11
Issue number22
DOIs
Publication statusPublished - Nov 2023

Keywords

  • Hilbert spaces
  • inertial term
  • maximal monotone
  • self-adaptive algorithm
  • split variational inclusion

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