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| Author | : Jörg Liesen |
| Publisher | : Numerical Mathematics and Scie |
| Total Pages | : 408 |
| Release | : 2013 |
| Genre | : Mathematics |
| ISBN | : 0199655413 |
Describes the principles and history behind the use of Krylov subspace methods in science and engineering. The outcome of the analysis is very practical and indicates what can and cannot be expected from the use of Krylov subspace methods, challenging some common assumptions and justifications of standard approaches.
| Author | : Iman Farahbakhsh |
| Publisher | : John Wiley & Sons |
| Total Pages | : 254 |
| Release | : 2020-09-15 |
| Genre | : Science |
| ISBN | : 1119618681 |
A succinct and complete explanation of Krylov subspace methods for solving systems of equations Krylov Subspace Methods with Application in Incompressible Fluid Flow Solvers is the most current and complete guide to the implementation of Krylov subspace methods for solving systems of equations with different types of matrices. Written in the simplest language possible and eliminating ambiguities, the text is easy to follow for post-grad students and applied mathematicians alike. The book covers a breadth of topics, including: The different methods used in solving the systems of equations with ill-conditioned and well-conditioned matrices The behavior of Krylov subspace methods in the solution of systems with ill-posed singular matrices Expertly supported with the addition of a companion website hosting computer programs of appendices The book includes executable subroutines and main programs that can be applied in CFD codes as well as appendices that support the results provided throughout the text. There is no other comparable resource to prepare the reader to use Krylov subspace methods in incompressible fluid flow solvers.
| Author | : H. A. van der Vorst |
| Publisher | : Cambridge University Press |
| Total Pages | : 242 |
| Release | : 2003-04-17 |
| Genre | : Mathematics |
| ISBN | : 9780521818285 |
Table of contents
| Author | : David S. Watkins |
| Publisher | : SIAM |
| Total Pages | : 452 |
| Release | : 2007-01-01 |
| Genre | : Mathematics |
| ISBN | : 9780898717808 |
The first in-depth, complete, and unified theoretical discussion of the two most important classes of algorithms for solving matrix eigenvalue problems: QR-like algorithms for dense problems and Krylov subspace methods for sparse problems. The author discusses the theory of the generic GR algorithm, including special cases (for example, QR, SR, HR), and the development of Krylov subspace methods. This book also addresses a generic Krylov process and the Arnoldi and various Lanczos algorithms, which are obtained as special cases. Theoretical and computational exercises guide students, step by step, to the results. Downloadable MATLAB programs, compiled by the author, are available on a supplementary Web site. Readers of this book are expected to be familiar with the basic ideas of linear algebra and to have had some experience with matrix computations. Ideal for graduate students, or as a reference book for researchers and users of eigenvalue codes.
| Author | : Yousef Saad |
| Publisher | : SIAM |
| Total Pages | : 537 |
| Release | : 2003-04-01 |
| Genre | : Mathematics |
| ISBN | : 0898715342 |
Mathematics of Computing -- General.
| Author | : Maxim A. Olshanskii |
| Publisher | : SIAM |
| Total Pages | : 257 |
| Release | : 2014-07-21 |
| Genre | : Mathematics |
| ISBN | : 1611973465 |
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.??
| Author | : Yousef Saad |
| Publisher | : SIAM |
| Total Pages | : 292 |
| Release | : 2011-01-01 |
| Genre | : Mathematics |
| ISBN | : 9781611970739 |
This revised edition discusses numerical methods for computing eigenvalues and eigenvectors of large sparse matrices. It provides an in-depth view of the numerical methods that are applicable for solving matrix eigenvalue problems that arise in various engineering and scientific applications. Each chapter was updated by shortening or deleting outdated topics, adding topics of more recent interest, and adapting the Notes and References section. Significant changes have been made to Chapters 6 through 8, which describe algorithms and their implementations and now include topics such as the implicit restart techniques, the Jacobi-Davidson method, and automatic multilevel substructuring.
| Author | : Anne Greenbaum |
| Publisher | : SIAM |
| Total Pages | : 225 |
| Release | : 1997-01-01 |
| Genre | : Mathematics |
| ISBN | : 089871396X |
Mathematics of Computing -- Numerical Analysis.
| Author | : A. R. Conn |
| Publisher | : SIAM |
| Total Pages | : 960 |
| Release | : 2000-01-01 |
| Genre | : Mathematics |
| ISBN | : 0898714605 |
Mathematics of Computing -- General.
| Author | : Gerard Meurant |
| Publisher | : Elsevier |
| Total Pages | : 777 |
| Release | : 1999-06-16 |
| Genre | : Mathematics |
| ISBN | : 0080529518 |
This book deals with numerical methods for solving large sparse linear systems of equations, particularly those arising from the discretization of partial differential equations. It covers both direct and iterative methods. Direct methods which are considered are variants of Gaussian elimination and fast solvers for separable partial differential equations in rectangular domains. The book reviews the classical iterative methods like Jacobi, Gauss-Seidel and alternating directions algorithms. A particular emphasis is put on the conjugate gradient as well as conjugate gradient -like methods for non symmetric problems. Most efficient preconditioners used to speed up convergence are studied. A chapter is devoted to the multigrid method and the book ends with domain decomposition algorithms that are well suited for solving linear systems on parallel computers.
