Iterative Methods for Linear Systems : Theory and Applications

Olshanskii, Maxim A.; Tyrtyshnikov, Eugene E.

ISBN 10: 1611973457 / ISBN 13: 9781611973457

Published by SIAM-Society for Industrial and Applied Mathematics, 2014

About this Item

Seller Inventory # 21878729-n

Bibliographic Details

Title: Iterative Methods for Linear Systems : ...

Publisher: SIAM-Society for Industrial and Applied Mathematics

Publication Date: 2014

Binding: Soft cover

Condition: New

About this title

Synopsis:

Iterative Methods for Linear Systems offers a mathematically rigorous introduction to fundamental iterative methods for systems of linear algebraic equations. The book distinguishes itself from other texts on the topic by providing a straightforward yet comprehensive analysis of the Krylov subspace methods, approaching the development and analysis of algorithms from various algorithmic and mathematical perspectives, and going beyond the standard description of iterative methods by connecting them in a natural way to the idea of preconditioning.

Audience: The book supplements standard texts on numerical mathematics for first-year graduate and advanced undergraduate courses and is suitable for advanced graduate classes covering numerical linear algebra and Krylov subspace and multigrid iterative methods. It will be useful to researchers interested in numerical linear algebra and engineers who use iterative methods for solving large algebraic systems.

Contents: Chapter 1: Krylov Subspace Methods; 1.1: Simple iterative methods; 1.2: Subspaces and iterative methods; 1.3: Analysis of the minimal residual method; 1.4: Analysis of the conjugate gradient method; Chapter 2: Toeplitz Matrices and Preconditioners; 2.1: Introduction to Toeplitz Matrices; 2.2: Preconditioners and applications; Chapter 3: Multigrid Preconditioners; 3.1: The introductory section; 3.2: Two-grid iteration; 3.3: Multigrid iteration; 3.4: Convergence analysis; Chapter 4: Preconditioners by Space Decomposition; 4.1: Space decomposition framework; 4.2: Grid decomposition methods; 4.3: Domain decomposition methods; 4.4: Convergence analysis for the Poisson problem; Chapter 5: Some Applications; 5.1: Multigrid preconditioners for singular-perturbed problems; 5.2: Preconditioners for certain problems of fluid mechanics; Bibliography; Index

About the Author:

Maxim A. Olshanskii is a professor in the Department of Mathematics at the University of Houston and an adjunct professor at Emory University and Moscow Institute of Physics and Technology. He is the Managing Editor of the Journal of Numerical Mathematics and 2001 recipient of the Young Scientists Award of the European Academy of Sciences.

Eugene E. Tyrtyshnikov is Director of the Institute of Numerical Mathematics of the Russian Academy of Sciences and Professor and Chairman at the Faculty of Computational Mathematics and Cybernetics of Moscow State University. He became a Corresponding Member of the Russian Academy of Sciences in 2006. He serves as associate editor of Linear Algebra and Its Applications and as a member of editorial boards of seven other journals.