Modified Hager-Zhang conjugate gradient methods via singular value analysis for solving monotone nonlinear equations with convex constraint

Jamilu Sabi'U, Abdullah Shah, Mohammed Yusuf Waziri, Kabiru Ahmed

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Following a recent attempt by Waziri et al. [2019] to find an appropriate choice for the nonnegative parameter of the Hager-Zhang conjugate gradient method, we have proposed two adaptive options for the Hager-Zhang nonnegative parameter by analyzing the search direction matrix. We also used the proposed parameters with the projection technique to solve convex constraint monotone equations. Furthermore, the global convergence of the methods is proved using some proper assumptions. Finally, the efficacy of the proposed methods is demonstrated using a number of numerical examples.

Original languageEnglish
Article number2050043
JournalInternational Journal of Computational Methods
Volume18
Issue number4
DOIs
StatePublished - May 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 World Scientific Publishing Company.

Keywords

  • Singular value
  • condition number
  • convex constraint
  • matrix analysis
  • monotone nonlinear equation
  • projection method

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computational Mathematics

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