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Iterative Methods for Sparse Linear Systems

Iterative Methods for Sparse Linear Systems

Iterative Methods for Sparse Linear Systems

2nd Edition
Yousef Saad, University of Minnesota
April 2003
Paperback
9780898715347
NZD$280.95
inc GST
Paperback

    Tremendous progress has been made in the scientific and engineering disciplines regarding the use of iterative methods for linear systems. The size and complexity of linear and nonlinear systems arising in typical applications has grown, meaning that using direct solvers for the three-dimensional models of these problems is no longer effective. At the same time, parallel computing, becoming less expensive and standardized, has penetrated these application areas. Iterative methods are easier than direct solvers to implement on parallel computers but require approaches and solution algorithms that are different from classical methods. This second edition gives an in-depth, up-to-date view of practical algorithms for solving large-scale linear systems of equations, including a wide range of the best methods available today. A new chapter on multigrid techniques has been added, whilst material throughout has been updated, removed or shortened. Numerous exercises have been added, as well as an updated and expanded bibliography.

    • Can be used to teach graduate-level courses on iterative methods for linear systems
    • Engineers and mathematicians will find its contents easily accessible, and practitioners and educators will value it as a helpful resource
    • The preface includes syllabi that can be used for either a semester- or quarter-length course in both mathematics and computer science

    Product details

    April 2003
    Paperback
    9780898715347
    184 pages
    247 × 178 × 28 mm
    0.929kg
    This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.

    Table of Contents

    • Preface
    • 1. Background in linear algebra
    • 2. Discretization of partial differential equations
    • 3. Sparse matrices
    • 4. Basic iterative methods
    • 5. Projection methods
    • 6. Krylov subspace methods Part I
    • 7. Krylov subspace methods Part II
    • 8. Methods related to the normal equations
    • 9. Preconditioned iterations
    • 10. Preconditioning techniques
    • 11. Parallel implementations
    • 12. Parallel preconditioners
    • 13. Multigrid methods
    • 14. Domain decomposition methods
    • Bibliography
    • Index.