Buch, Englisch, 776 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 1255 g
Buch, Englisch, 776 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 1255 g
ISBN: 978-0-444-50169-1
Verlag: Elsevier Science & Technology
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.
Autoren/Hrsg.
Fachgebiete
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
- Mathematik | Informatik Mathematik Mathematische Analysis Differentialrechnungen und -gleichungen
- Mathematik | Informatik Mathematik Algebra Homologische Algebra
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
Weitere Infos & Material
Introductory MaterialGaussian elimination for general linear systemsGaussian elimination for sparse linear systemsFast solvers for separable PDEsClassical iterative methodsThe conjugate gradient and related methodsKrylov methods for non--symmetric systemsPreconditioningMultigrid methods
