Skip to main content

Iterationsverfahren zur Lösung großer linearer Gleichungssysteme, einige weitere Verfahren

  • Chapter
Numerische Mathematik 2

Part of the book series: Springer-Lehrbuch ((SLB))

  • 422 Accesses

Zusammenfassung

Viele praktische Probleme führen zu der Aufgabe, sehr große lineare Gleichungssyteme Ax = b zu lösen, bei denen glücklicherweise die Matrix A nur schwach besetzt ist, d. h. nur relativ wenige nicht verschwindende Komponenten besitzt. Solche Gleichungssysteme erhält man z. B. bei der Anwendung von Differenzenverfahren oder finite-element Methoden zur näherungsweisen Lösung von Randwertaufgaben bei partiellen Differentialgleichungen. Die üblichen Eliminationsverfahren [s. Kapitel 4] können hier nicht ohne weiteres zur Lösung verwandt werden, weil sie ohne besondere Maßnahmen gewöhnlich zur Bildung von mehr oder weniger voll besetzten Zwischenmatrizen führen und deshalb die Zahl der zur Lösung erforderlichen Rechenoperationen auch für die heutigen Rechner zu groß wird, abgesehen davon, daß die Zwischenmatrizen nicht mehr in die üblicherweise verfügbaren Maschinenspeicher passen.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Literatur zu Kapitel 8

  • Arnoldi, W.E. (1951): The principle of minimized iteration in the solution of the matrix eigenvalue problem Quart. Appl. Math. 9 17–29

    MathSciNet  MATH  Google Scholar 

  • Axelsson, O. (1977): Solution of linear systems of equations: Iterative methods. In: Barker (1977).

    Google Scholar 

  • Axelsson, O. (1994): Iterative Solution Methods Cambridge, UK: Cambridge University Press.

    Book  MATH  Google Scholar 

  • Barker, V.A. (Ed.) (1977): Sparse Matrix techniques. Lecture Notes in Mathematics Vol. 572, Berlin-Heidelberg-New York: Springer.

    Book  MATH  Google Scholar 

  • Braess, D. (1997): Finite Elemente. Berlin-Heidelberg-New York: Springer

    MATH  Google Scholar 

  • Bramble, J.H. (1993): Multigrid Methods. Harlow: Longman.

    MATH  Google Scholar 

  • Brandt, A. (1977): Multi-level adaptive solutions to boundary value problems Math. of Comput. 31 333–390

    Article  MATH  Google Scholar 

  • Briggs, W.L. (1987) A Multigrid Tutorial. Philadelphia: SIAM

    MATH  Google Scholar 

  • Buneman, O. (1969): A compact non-iterative Poisson solver. Stanford University, Institute for Plasma Research Report Nr. 294, Stanford, CA.

    Google Scholar 

  • Buzbee, B.L., Dorr, F.W. (1974): The direct solution of the biharmonic equation on rectangular regions and the Poisson equation on irregular regions. SIAM J. Numer. Anal 11, 753–763.

    Article  MathSciNet  MATH  Google Scholar 

  • F.W., George, J.A., Golub, G.H. (1971): The direct solution of the discrete Poisson equation on irregular regions SIAM J. Numer. Anal. 8 722–736.

    Article  MathSciNet  MATH  Google Scholar 

  • Golub, G.H., Nielson, C.W. (1970): On direct methods for solving Poisson’s equations SIAM J. Numer. Anal. 7 627–656

    Article  MathSciNet  MATH  Google Scholar 

  • Chan, T.F., Glowinski, R., Periaux, J., Widlund, O. (Eds.) (1989): Proceedings of the Second International Symposium on Domain Decomposition Methods. Philadelphia: SIAM.

    Google Scholar 

  • Fletcher, R. (1974). Conjugate gradient methods for indefinite systems. In: G.A. Watson (ed.), Proceedings of the Dundee Biennial Conference on Numerical Analysis 1974, p. 73–89. New York: Springer-Verlag 1975.

    Google Scholar 

  • Forsythe, G.E., Moler, C.B. (1967): Computer Solution of Linear Algebraic Systems. Series in Automatic Computation. Englewood Cliffs, N.J.: Prentice Hall.

    Google Scholar 

  • Freund, R.W., Nachtigal, N.M. (1991): QMR: a quasi-minimal residual method for non-Hermitian linear systems. Numerische Mathematik 60, 315–339.

    Article  MathSciNet  MATH  Google Scholar 

  • George, A. (1973): Nested dissection of a regular finite element mesh. SIAM J. Numer. Anal 10, 345–363.

    Article  MATH  Google Scholar 

  • Glowinski, R., Golub, G.H., Meurant, G.A., Periaux, J. (Eds.) (1988): Proceedings of the First International Symposium on Domain Decomposition Methods for Partial Differential Equations. Philadelphia: SIAM.

    Google Scholar 

  • Hackbusch, W. (1985): Multigrid Methods and Applications. Berlin-Heidelberg-New York: Springer-Verlag.

    Book  Google Scholar 

  • Trottenberg, U. (Eds.) (1982): Multigrid Methods. Lecture Notes in Mathematics. Vol. 960. Berlin-Heidelberg-New York: Springer-Verlag.

    MATH  Google Scholar 

  • Hestenes, M.R., Stiefel, E. (1952): Methods of conjugate gradients for solving linear systems. Nat. Bur. Standards, J. of Res. 49, 409–436.

    Article  MathSciNet  MATH  Google Scholar 

  • Hockney, R.W. (1969): The potential calculation and some applications. Methods of Computational Physics 9 136–211. New York, London: Academic Press.

    Google Scholar 

  • Householder, A.S. (1964): The Theory of Matrices in Numerical Analysis. New York: Blaisdell Publ. Comp.

    MATH  Google Scholar 

  • Keyes, D.E., Gropp, W.D. (1987): A comparison of domain decomposition techniques for elliptic partial differential equations. SIAM J. Sci. Statist. Comput 8, s166 – s202.

    Article  MathSciNet  Google Scholar 

  • Lanczos, C. (1950): An iteration method for the solution of the eigenvalue problem of linear differential and integral equations. J. Res. Nat. Bur. Standards 45, 255-282.

    Article  MathSciNet  Google Scholar 

  • Lanczos, C. (1952): Solution of systems of linear equations by minimized iterations. J. Res. Nat. Bur. Standards 49, 33–53.

    Article  MathSciNet  Google Scholar 

  • McCormick, S. (1987): Multigrid Methods. Philadelphia: SIAM.

    Book  MATH  Google Scholar 

  • Meijerink, J.A., van der Vorst, H.A. (1977): An iterative solution method for linear systems of which the coefficient matrix is a symmetric M-matrix. Math. Comp 31, 148–162.

    MathSciNet  MATH  Google Scholar 

  • O’Leary, D.P., Widlund, O. (1979): Capacitance matrix methods for the Helmholtz equation on general three-dimensional regions. Math. Comp 33, 849–879.

    Google Scholar 

  • Paige, C.C., Saunders, M.A. (1975): Solution of sparse indefinite systems of linear equations. SIAM J. Numer. Analysis 12, 617–624.

    Article  MathSciNet  MATH  Google Scholar 

  • Proskurowski, W., Widlund, O. (1976): On the numerical solution of Helmholtz’s equation by the capacitance matrix method. Math. Comp 30, 433–468.

    MathSciNet  MATH  Google Scholar 

  • Quarteroni, A., Valli, A. (1997): Numerical Approximation of Partial Differential Equations. 2nd Ed., Berlin-Heidelberg-New York: Springer.

    Google Scholar 

  • Reid, J.K. (Ed.) (1971 a): Large Sparse Sets of Linear Equations London, New York: Academic Press. (1971 b): On the method of conjugate gradients for the solution of large sparse systems of linear equations. In: Reid (1971 a), 231–252.

    Google Scholar 

  • Rice, J.R., Boisvert, R.F. (1984): Solving Elliptic Problems Using ELLPACK. BerlinHeidelberg-New York: Springer.

    Google Scholar 

  • Saad, Y. (1996): Iterative Methods for Sparse Linear Systems. Boston: PWS Publishing Company.

    MATH  Google Scholar 

  • Schultz, M.H (1986): GMRES: a generalized minimal residual algorithm

    Google Scholar 

  • for solving nonsymmetric linear systems. SIAM J. Scientific and Statistical Computing 7 856–869.

    Google Scholar 

  • Schröder, J., Trottenberg, U. (1973): Reduktionsverfahren für Differenzengleichungen bei Randwertaufgaben I. Numer.Math 22, 37–68.

    Article  MathSciNet  MATH  Google Scholar 

  • Reutersberg, H. (1976): Reduktionsverfahren für Differenzengleichungen bei Randwertaufgaben II. Numer. Math 26, 429–459.

    Google Scholar 

  • Sonneveldt, P. (1989): CGS, a fast Lanczos-type solver for nonsymmetric linear systems. SIAM J. Scientific and Statistical Computing 10, 36–52.

    Article  Google Scholar 

  • Swarztrauber, P.N. (1977): The methods of cyclic reduction, Fourier analysis and the FACR algorithm for the discrete solution of Poisson’s equation on a rectangle. SIAM Review 19, 490–501.

    Article  MathSciNet  MATH  Google Scholar 

  • van der Vorst (1992): Bi-CGSTAB: A fast and smoothly converging variant of Bi-CG for the solution of non-symmetric linear systems. SIAM J Scientific and Statistical Computing 12, 631–644.

    Google Scholar 

  • Varga, R.S. (1962): Matrix Iterative Analysis. Series in Automatic Computation. Englewood Cliffs: Prentice Hall.

    Google Scholar 

  • Wachspress, E.L. (1966): Iterative Solution of Elliptic Systems and Application to the Neutron Diffusion Equations of Reactor Physics. Englewood Cliffs, N.J.: Prentice-Hall.

    Google Scholar 

  • Wilkinson, J.H., Reinsch, C. (1971): Linear Algebra. Handbook for Automatic Computation, Vol. II. Grundlehren der mathematischen Wissenschaften in Einzeldarstellungen, Bd. 186. Berlin-Heidelberg-New York: Springer.

    Google Scholar 

  • Young, D.M. (1971): Iterative Solution of Large Linear Systems. Computer Science and Applied Mathematics. New York: Academic Press.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Stoer, J., Bulirsch, R. (2000). Iterationsverfahren zur Lösung großer linearer Gleichungssysteme, einige weitere Verfahren. In: Numerische Mathematik 2. Springer-Lehrbuch. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-09025-1_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-09025-1_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67644-7

  • Online ISBN: 978-3-662-09025-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics