Krylov Methods For Nonsymmetric Linear Systems PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Krylov Methods For Nonsymmetric Linear Systems PDF full book. Access full book title Krylov Methods For Nonsymmetric Linear Systems.

Krylov Methods for Nonsymmetric Linear Systems

Krylov Methods for Nonsymmetric Linear Systems
Author: Gérard Meurant
Publisher: Springer Nature
Total Pages: 686
Release: 2020-10-02
Genre: Mathematics
ISBN: 3030552519

Download Krylov Methods for Nonsymmetric Linear Systems Book in PDF, ePub and Kindle

This book aims to give an encyclopedic overview of the state-of-the-art of Krylov subspace iterative methods for solving nonsymmetric systems of algebraic linear equations and to study their mathematical properties. Solving systems of algebraic linear equations is among the most frequent problems in scientific computing; it is used in many disciplines such as physics, engineering, chemistry, biology, and several others. Krylov methods have progressively emerged as the iterative methods with the highest efficiency while being very robust for solving large linear systems; they may be expected to remain so, independent of progress in modern computer-related fields such as parallel and high performance computing. The mathematical properties of the methods are described and analyzed along with their behavior in finite precision arithmetic. A number of numerical examples demonstrate the properties and the behavior of the described methods. Also considered are the methods’ implementations and coding as Matlab®-like functions. Methods which became popular recently are considered in the general framework of Q-OR (quasi-orthogonal )/Q-MR (quasi-minimum) residual methods. This book can be useful for both practitioners and for readers who are more interested in theory. Together with a review of the state-of-the-art, it presents a number of recent theoretical results of the authors, some of them unpublished, as well as a few original algorithms. Some of the derived formulas might be useful for the design of possible new methods or for future analysis. For the more applied user, the book gives an up-to-date overview of the majority of the available Krylov methods for nonsymmetric linear systems, including well-known convergence properties and, as we said above, template codes that can serve as the base for more individualized and elaborate implementations.


Iterative Methods for Sparse Linear Systems

Iterative Methods for Sparse Linear Systems
Author: Yousef Saad
Publisher: SIAM
Total Pages: 537
Release: 2003-04-01
Genre: Mathematics
ISBN: 0898715342

Download Iterative Methods for Sparse Linear Systems Book in PDF, ePub and Kindle

Mathematics of Computing -- General.


Iterative Krylov Methods for Large Linear Systems

Iterative Krylov Methods for Large Linear Systems
Author: H. A. van der Vorst
Publisher: Cambridge University Press
Total Pages: 242
Release: 2003-04-17
Genre: Mathematics
ISBN: 9780521818285

Download Iterative Krylov Methods for Large Linear Systems Book in PDF, ePub and Kindle

Table of contents


A Hybrid Chebyshev Krylov Subspace Algorithm for Solving Nonsymmetric Systems of Linear Equations

A Hybrid Chebyshev Krylov Subspace Algorithm for Solving Nonsymmetric Systems of Linear Equations
Author: H. C. Elman
Publisher:
Total Pages: 23
Release: 1984
Genre:
ISBN:

Download A Hybrid Chebyshev Krylov Subspace Algorithm for Solving Nonsymmetric Systems of Linear Equations Book in PDF, ePub and Kindle

This document presents an iterative method for solving large sparse nonsymmetric linear systems of equations that enhances Manteuffel's adaptive Chebyshev method with a conjugate gradient-like method. The new method replaces the modified power method for computing needed eigenvalue estimates with Arnoldi's method, which can be used to simultaneously compute eigenvalues and to improve the approximate solution. Convergence analysis and numerical experiments suggest that the method is more efficient than the original adaptive Chebyshev algorithm. (Author).