Direct Methods for Sparse Linear Systems
Direct Methods for Sparse Linear Systems
£56.00
GBPComputational scientists often encounter problems requiring the solution of sparse systems of linear equations. Attacking these problems efficiently requires an in-depth knowledge of the underlying theory, algorithms, and data structures found in sparse matrix software libraries. Here, Davis presents the fundamentals of sparse matrix algorithms to provide the requisite background. The book includes CSparse, a concise downloadable sparse matrix package that illustrates the algorithms and theorems presented in the book and equips readers with the tools necessary to understand larger and more complex software packages. With a strong emphasis on MATLAB® and the C programming language, Direct Methods for Sparse Linear Systems equips readers with the working knowledge required to use sparse solver packages and write code to interface applications to those packages. The book also explains how MATLAB performs its sparse matrix computations.
- Includes CSparse, a concise downloadable sparse matrix package that illustrates the algorithms and theorems presented in the book.
- Equips readers with the working knowledge required to use sparse solver packages and write code to interface applications to those packages.
- Everything you wanted to know but never dared to ask about modern direct linear solvers
Reviews & endorsements
'Everything you wanted to know but never dared to ask about modern direct linear solvers.' Chen Greif, University of British Columbia
'Overall, the book is magnificent. It fills a long-felt need for an accessible textbook on modern sparse direct methods. Its choice of scope is excellent …' John Gilbert, University of California, Santa Barbara
Product details
September 2006Paperback
9780898716139
184 pages
255 × 178 × 13 mm
0.422kg
This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
Table of Contents
- Preface
- 1. Introduction
- 2. Basic algorithms
- 3. Solving triangular systems
- 4. Cholesky factorization
- 5. Orthogonal methods
- 6. LU factorization
- 7. Fill-reducing orderings
- 8. Solving sparse linear systems
- 9. CSparse
- 10. Sparse matrices in MATLAB
- Appendix: Basics of the C programming language
- Bibliography
- Index.
