This is the authors' abstract. We don't add key points for this paper.
We consider a class of iterative algorithms for solving systems of linear equations where the coefficient matrix is nonsymmetric with positive-definite symmetric part. The algorithms are modelled after the conjugate gradient method, and are well suited for large sparse systems. They do not make use of any associated symmetric problems. Convergence results and error bounds are presented.
Answers are grounded in this paper and cite their sources.
No takes yet. Share an insight, caveat, or question.
Eisenstat et al. (1983) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: