On the order of convergence of preconditioned nonlinear conjugate gradient methods

M. Al-Baali*, R. Fletcher

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

An analysis is given of preconditioned nonlinear conjugate gradient methods in which the preconditioning matrix is the exact Hessian matrix at each iteration (or a nearby matrix). It is shown that the order of convergence of certain preconditioned methods is less than that of Newton's method when exact line searches are used, and an example is given.

Original languageEnglish
Pages (from-to)658-665
Number of pages8
JournalSIAM Journal on Scientific Computing
Volume17
Issue number3
DOIs
Publication statusPublished - May 1996
Externally publishedYes

Keywords

  • Conjugate gradient methods
  • Newton's method
  • Preconditioning
  • Unconstrained optimization

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics

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