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Eigenvalue Estimates for Preconditioned Saddle Point Matrices

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Large-Scale Scientific Computing (LSSC 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2907))

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Abstract

Eigenvalue bounds for saddle point matrices on symmetric or, more generally, nonsymmetric form are derived and applied for preconditioned versions of the matrices. The preconditioners enable efficient iterative solution of the corresponding linear systems.

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Author information

Authors and Affiliations

  1. University of Nijmegen, Nijmegen, The Netherlands

    Owe Axelsson

Authors
  1. Owe Axelsson
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Editor information

Editors and Affiliations

  1. Institute for Parallel Processing, Bulgarian Academy of Sciences, Acad. G. Bonchev, Bl. 25A, 1113, Sofia, Bulgaria

    Ivan Lirkov

  2. Institute for Parallel Processing, Bulgarian Academy of Sciences, Acad. G. Bonchev Str. Bl. 25-A, 1113, Sofia, Bulgaria

    Svetozar Margenov

  3. Informatics & Mathematical Modeling, Technical University of Denmark, DK-2800, Lyngby, Denmark

    Jerzy Waśniewski

  4. Center of Applied Mathematics and Informatics, University of Rousse, 7017, Rousse, Bulgaria

    Plamen Yalamov

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© 2004 Springer-Verlag Berlin Heidelberg

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Axelsson, O. (2004). Eigenvalue Estimates for Preconditioned Saddle Point Matrices. In: Lirkov, I., Margenov, S., Waśniewski, J., Yalamov, P. (eds) Large-Scale Scientific Computing. LSSC 2003. Lecture Notes in Computer Science, vol 2907. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24588-9_1

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  • DOI: https://doi.org/10.1007/978-3-540-24588-9_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21090-0

  • Online ISBN: 978-3-540-24588-9

  • eBook Packages: Springer Book Archive

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