Conjugate gradient methods for indefinite systems

  • R. Fletcher
Conference paper
Part of the Lecture Notes in Mathematics book series (LNM, volume 506)

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bunch, J.R., and Parlett, B.N., Direct methods for solving symetric indefinite systems of linear equations, S. I. A. M. J. Numer. Anal., Vol. 8, 1971, pp. 639–655.MathSciNetCrossRefGoogle Scholar
  2. 2.
    Hestenes, M.R., and Stiefel, E., Methods of Conjugate Gradients for Solving Linear Systems, J. Res. Nat. Bur. Standards, Vol. 49, 1952, pp. 409–436.MathSciNetCrossRefMATHGoogle Scholar
  3. 3.
    Lanczos, C., An Iteration Method for the Solution of the Eigenvalue Problem of Linear Differential and Integral Operators, J. Res. Nat. Bur. Standards, Vol. 45, 1950, pp. 255–282.MathSciNetCrossRefGoogle Scholar
  4. 4.
    Lawson, C.L., Sparse Matrix Methods Based on Orthogonality and Conjugacy, Jet Propulsion Lab., Tech. Memo. 33–627, 1973.Google Scholar
  5. 5.
    Luenberger, D.G., Hyperbolic pairs in the method of conjugate gradients, S. I. A. M. J. Appl. Math., Vol. 17, 1969, pp. 1263–1267.MathSciNetCrossRefMATHGoogle Scholar
  6. 6.
    Paige, C.C., and Saunders, M.A., Solution of sparse indefinite systems of equations and least squares problems, Stanford University Report, STAN-CS-73-399, 1973.Google Scholar
  7. 7.
    Reid, J.K., On the Method of Conjugate Gradients for the Solution of Large Sparse Systems of Linear Equations, pp. 231–254 in Large Sparse Systems of Linear Equations, ed. J.K. Reid, Academic Press, London, 1971.Google Scholar
  8. 8.
    Rutishauser, H., Theory of gradient methods, Chapter 2 of Refined iterative methods for computation of the solution and the eigenvalues of self-adjoint boundary value problems, by M. Engeli, Th. Ginsburg, H. Rutishauser, and E. Stiefel, Birkhaüser, Basel, 1959.Google Scholar

Copyright information

© Springer-Verlag 1976

Authors and Affiliations

  • R. Fletcher

There are no affiliations available

Personalised recommendations