Conjugate gradient algorithms and finite element methods.

KRIZEK, M. , P. NEITTAANMÄKI, R. GLOWINSKI and S. KOROTOV (Eds).

ISBN 10: 3540213198 / ISBN 13: 9783540213192

Published by Springer, Berlin, 2004

About this Item

24 cm. original hardcover. 382 pp. ills, diagrams. references. index. "Scientific Computation". -very good. 800g.

Seller Inventory # 71507

Bibliographic Details

• Title: Conjugate gradient algorithms and finite element methods.
• Publisher: Springer, Berlin
• Publication Date: 2004
• Language: English
• ISBN 10: 3540213198
• ISBN 13: 9783540213192
• Binding: Hardcover

About this title

Synopsis

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 complicated, direct and inverse, multidemensional 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.

From the Back Cover

 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.