Description

Book Synopsis
Iterative methods use successive approximations to obtain more accurate solutions. Iterative Methods and Preconditioners for Systems of Linear Equations
  • presents historical background,
  • derives complete convergence estimates for all methods,
  • illustrates and provides Matlab codes for all methods, and
  • studies and tests all preconditioners first as stationary iterative solvers.

This textbook is appropriate for undergraduate and graduate students in need of an overview or of deeper knowledge about iterative methods. It can be used in courses on Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory. Scientists and engineers interested in new topics and applications will also find the text useful.

Iterative Methods and Preconditioners for Systems

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Order before 4pm tomorrow for delivery by Mon 19 Jan 2026.

A Paperback / softback by Gabriele Ciaramella, Martin J. Gander

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    View other formats and editions of Iterative Methods and Preconditioners for Systems by Gabriele Ciaramella

    Publisher: Society for Industrial & Applied Mathematics,U.S.
    Publication Date: 28/02/2022
    ISBN13: 9781611976892, 978-1611976892
    ISBN10: 1611976898
    Also in:
    Applied mathematics Differential calculus and equations Numerical analysis

    Description

    Book Synopsis
    Iterative methods use successive approximations to obtain more accurate solutions. Iterative Methods and Preconditioners for Systems of Linear Equations
    • presents historical background,
    • derives complete convergence estimates for all methods,
    • illustrates and provides Matlab codes for all methods, and
    • studies and tests all preconditioners first as stationary iterative solvers.

    This textbook is appropriate for undergraduate and graduate students in need of an overview or of deeper knowledge about iterative methods. It can be used in courses on Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory. Scientists and engineers interested in new topics and applications will also find the text useful.

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