Minimization properties and short recurrences

1Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Two algorithms characterized by a short recurrence as well as a minimization property in the energy norm are derived by choosing suitable preconditioning matrices for certain step-dependent preconditioned conjugate Krylov subspace (CKS) algorithms. It is shown that the two methods are also equivalent to two special truncated generalized CG algorithms. Therefore, it is possible to state a minimization property for truncated generalized CG algorithms in a k-dimensional space. Numerical comparison with other generalized CG algorithms requiring the same amount of storage shows that the derived methods are competitive and for certain problems faster.

Cite

CITATION STYLE

APA

Wagner, B., & Weiss, R. (1999). Minimization properties and short recurrences. Applied Numerical Mathematics, 30(2), 175–190. https://doi.org/10.1016/S0168-9274(98)00109-3

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free