Conjugate gradient-like algorithms for solving nonsymmetric linear systems

1985183 citationsJournal Articlebronze Open Access

Authors

Abstract

This paper presents a unified formulation of a class of the conjugate gradient-like algorithms for solving nonsymmetric linear systems. The common framework is the Petrov-Galerkin method on Krylov subspaces. We discuss some practical points concerning the methods and point out some of the interrelations between them.

Topics & Keywords

Matrix Theory and Algorithms Statistical and numerical algorithms Numerical methods in inverse problems

Publication Details

Published in: Mathematics of Computation

Volume 44, Issue 170, pp. 417-424

DOI: 10.1090/s0025-5718-1985-0777273-9

Field-Weighted Citation Impact: 6.23

Command Palette

Conjugate gradient-like algorithms for solving nonsymmetric linear systems

Authors

Abstract

Topics & Keywords

Publication Details