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.