Systems Optimization Laboratory
Stanford, CA 94305-4121 USA
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cgLanczos: CG method for positive definite Ax = b
- AUTHOR:
M. A. Saunders
- CONTRIBUTORS: C. C. Paige, Tung-Yu Wu, Ruijie Zhou
- CONTENTS: A MATLAB implementation of the Conjugate Gradient method
for linear equations: Solve
\[
Ax = b,
\]
where the matrix \(A\) is symmetric and positive definite.
Special feature: Returns an estimate of diag(\(A^{-1}\)).
- REFERENCES:
C. C. Paige and M. A. Saunders (1975).
Solution of sparse indefinite systems of linear equations,
SINUM 12, 617--629.
- RELEASE:
22 Oct 2007: cgLanczos.m (first version) implemented to assist
Giannis Chantas (chanjohn@cs.uoi.gr),
Dept of Computer Science, University of Ioannina, Greece.
18 Nov 2013: cgLanczos2.m derived from CME 338 class project of
Tung-Yu Wu and Ruijie Zhou, Stanford University.
Calling sequence matches Matlab's pcg.
Better stopping rules implemented.
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