Home Algorithms for Sparse Linear Systems by Jennifer Scott; Miroslav Tůma (ISBN: 9783031258190)

Stock photo: cover may vary

Algorithms for Sparse Linear Systems Paperback -

Name: Algorithms for Sparse Linear Systems
Price: 34.99 GBP
Availability: InStock
Author: Scott, Jennifer/ Tuma, Miroslav
ISBN: 9783031258190

by Jennifer Scott; Miroslav Tůma

Add to wish list

Browse more copies for sale ↓

Reader reviews for Algorithms for Sparse Linear Systems

Write a review for this book

Important Terms and Guidelines

Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
Reviews must be at least 140 characters in length.
Please do not reveal critical plot elements.
This is not a help line. Contact customer support if you need help.

Your review must not include:

Obscenities, discriminatory language, or other insulting language not suitable for public domain
Advertisements, “spam” content, or references to other products, offers or websites.
Email addresses, URLs, phone numbers, physical addresses or other contact information.
Overly critical comments about other reviews or reviewers
Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
Availability, price, or alternative ordering/shipping information

From the publisher

Large sparse linear systems of equations are ubiquitous in science, engineering and beyond. This open access monograph focuses on factorization algorithms for solving such systems. It presents classical techniques for complete factorizations that are used in sparse direct methods and discusses the computation of approximate direct and inverse factorizations that are key to constructing general-purpose algebraic preconditioners for iterative solvers. A unified framework is used that emphasizes the underlying sparsity structures and highlights the importance of understanding sparse direct methods when developing algebraic preconditioners. Theoretical results are complemented by sparse matrix algorithm outlines.
This monograph is aimed at students of applied mathematics and scientific computing, as well as computational scientists and software developers who are interested in understanding the theory and algorithms needed to tackle sparse systems. It is assumed that the reader has completed a basic course in linear algebra and numerical mathematics.

From the rear cover

Large sparse linear systems of equations are ubiquitous in science, engineering and beyond. This open access monograph focuses on factorization algorithms for solving such systems. It presents classical techniques for complete factorizations that are used in sparse direct methods and discusses the computation of approximate direct and inverse factorizations that are key to constructing general-purpose algebraic preconditioners for iterative solvers. A unified framework is used that emphasizes the underlying sparsity structures and highlights the importance of understanding sparse direct methods when developing algebraic preconditioners. Theoretical results are complemented by sparse matrix algorithm outlines.
This monograph is aimed at students of applied mathematics and scientific computing, as well as computational scientists and software developers who are interested in understanding the theory and algorithms needed to tackle sparsesystems. It is assumed that the reader has completed a basic course in linear algebra and numerical mathematics.

Details

Title Algorithms for Sparse Linear Systems
Author Jennifer Scott; Miroslav Tůma
Binding Paperback
Pages 242
Volumes 1
Language ENG
Publisher Birkhauser
Illustrated Yes
ISBN 9783031258190 / 3031258193
Weight 0.83 lbs (0.38 kg)
Dimensions 9.25 x 6.1 x 0.55 in (23.50 x 15.49 x 1.40 cm)
Category Mathematics

About the author

Jennifer Scott is a Professor of Mathematics at the University of Reading and an Individual Merit Research Fellow at the Rutherford Appleton Laboratory. She is a SIAM Fellow and a Fellow of the Institute of Mathematics and its Applications. She is the author of many widely used sparse matrix packages that are available as part of the HSL Mathematical Software Library.
Miroslav Tuma is a Professor and Head of the Department of Numerical Mathematics at Charles University and was formerly a Professor at the Institute of Computer Science of the Academy of Sciences of the Czech Republic. His research has included important contributions to the development of algebraic preconditioners for iterative solvers. He was the recipient of a SIAM outstanding paper prize for his work on sparse approximate inverse preconditioners.

More Copies for Sale

Stock photo: cover may vary