Conjugate Gradient Algorithms and Finite Element Methods

  • Michal Křížek
  • Pekka Neittaanmäki
  • Sergey Korotov
  • Roland Glowinski

Part of the Scientific Computation book series (SCIENTCOMP)

Table of contents

  1. Front Matter
    Pages I-XV
  2. Foundations

    1. Front Matter
      Pages 1-1
    2. Michal Křížek, Sergey Korotov
      Pages 25-43
  3. Aspects of Conjugate Gradient Algorithms

    1. Front Matter
      Pages 45-45
    2. Jan Brandts, Henk van der Vorst
      Pages 47-68
    3. Ladislav Lukšan, Ctirad Matonoha, Jan Vlček
      Pages 131-145
  4. Finite Element Meshes

    1. Front Matter
      Pages 147-147
    2. Sergey Korotov, Jacek Stańdo
      Pages 149-160
    3. Michal Křížek, Jakub Šolc
      Pages 161-170
    4. Pekka Neittaanmäki, Sergey Korotov, Janne Martikainen
      Pages 171-181
  5. Applications to the Solution of Linear and Nonlinear Partial Differential Equations

  6. Advanced Applications: From Image Processing to Computational Physics

  7. Back Matter
    Pages 369-384

About this book


 The position taken in this collection of pedagogically written essays is that conjugate gradient algorithms and finite element methods complement each other extremely well.  Via their combinations practitioners have been able to solve differential equations and multidimensional problems modeled by ordinary or partial differential equations and inequalities, not necessarily linear, optimal control and optimal design being part of these problems. The  aim of this book is to present both methods in the context of complicated problems modeled by linear and nonlinear partial differential equations, to provide an in-depth discussion on their implementation aspects. The authors show that conjugate gradient methods and finite element methods apply to the solution of real-life problems. They address graduate students as well as experts in scientific computing.


Domain Decomposition Maxwell's equations Triangulation algorithm algorithms construction control differential equation finite element method multiphase flow operator optimization partial differential equation scientific computing simulation

Editors and affiliations

  • Michal Křížek
    • 1
  • Pekka Neittaanmäki
    • 2
  • Sergey Korotov
    • 2
  • Roland Glowinski
    • 3
  1. 1.Mathematical InstituteAcademy of SciencesPragueCzech Republic
  2. 2.Department of Mathematical Information TechnologyUniversity of JyväskyläJyväskyläFinland
  3. 3.Department of MathematicsUniversity of HoustonHoustonUSA

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2004
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-62159-8
  • Online ISBN 978-3-642-18560-1
  • Series Print ISSN 1434-8322
  • Buy this book on publisher's site
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