Author : Are Magnus Bruaset
Publisher : Routledge
Page : 180 pages
File Size : 23,89 MB
Release : 2018-12-13
Category : Mathematics
ISBN : 1351469363
The problem of solving large, sparse, linear systems of algebraic equations is vital in scientific computing, even for applications originating from quite different fields. A Survey of Preconditioned Iterative Methods presents an up to date overview of iterative methods for numerical solution of such systems. Typically, the methods considered are w
Author : Yousef Saad
Publisher : SIAM
Page : 537 pages
File Size : 10,87 MB
Release : 2003-04-01
Category : Mathematics
ISBN : 0898715342
Mathematics of Computing -- General.
Author : Daniele Bertaccini
Publisher : CRC Press
Page : 321 pages
File Size : 39,80 MB
Release : 2018-02-19
Category : Mathematics
ISBN : 1351649612
This book describes, in a basic way, the most useful and effective iterative solvers and appropriate preconditioning techniques for some of the most important classes of large and sparse linear systems. The solution of large and sparse linear systems is the most time-consuming part for most of the scientific computing simulations. Indeed, mathematical models become more and more accurate by including a greater volume of data, but this requires the solution of larger and harder algebraic systems. In recent years, research has focused on the efficient solution of large sparse and/or structured systems generated by the discretization of numerical models by using iterative solvers.
Author : Åke Björck
Publisher : Springer
Page : 812 pages
File Size : 35,49 MB
Release : 2014-10-07
Category : Mathematics
ISBN : 3319050893
Matrix algorithms are at the core of scientific computing and are indispensable tools in most applications in engineering. This book offers a comprehensive and up-to-date treatment of modern methods in matrix computation. It uses a unified approach to direct and iterative methods for linear systems, least squares and eigenvalue problems. A thorough analysis of the stability, accuracy, and complexity of the treated methods is given. Numerical Methods in Matrix Computations is suitable for use in courses on scientific computing and applied technical areas at advanced undergraduate and graduate level. A large bibliography is provided, which includes both historical and review papers as well as recent research papers. This makes the book useful also as a reference and guide to further study and research work.
Author : Ke Chen
Publisher : Cambridge University Press
Page : 616 pages
File Size : 37,36 MB
Release : 2005-07-14
Category : Mathematics
ISBN : 9780521838283
A comprehensive introduction to preconditioning techniques, now an essential part of successful and efficient iterative solutions of matrices.
Author : H. A. van der Vorst
Publisher : Cambridge University Press
Page : 242 pages
File Size : 42,96 MB
Release : 2003-04-17
Category : Mathematics
ISBN : 9780521818285
Table of contents
Author : István Faragó
Publisher : Nova Publishers
Page : 424 pages
File Size : 24,21 MB
Release : 2002
Category : Mathematics
ISBN : 9781590333761
Numerical Solution of Nonlinear Elliptic Problems Via Preconditioning Operators - Theory & Applications
Author : Yousef Saad
Publisher : SIAM
Page : 546 pages
File Size : 17,17 MB
Release : 2003-01-01
Category : Mathematics
ISBN : 9780898718003
Since the first edition of this book was published in 1996, tremendous progress has been made in the scientific and engineering disciplines regarding the use of iterative methods for linear systems. The size and complexity of the new generation of linear and nonlinear systems arising in typical applications has grown. Solving the three-dimensional models of these problems using direct solvers is no longer effective. At the same time, parallel computing has penetrated these application areas as it became less expensive and standardized. Iterative methods are easier than direct solvers to implement on parallel computers but require approaches and solution algorithms that are different from classical methods. Iterative Methods for Sparse Linear Systems, Second Edition gives an in-depth, up-to-date view of practical algorithms for solving large-scale linear systems of equations. These equations can number in the millions and are sparse in the sense that each involves only a small number of unknowns. The methods described are iterative, i.e., they provide sequences of approximations that will converge to the solution.
Author : Mary Catherine Hill
Publisher :
Page : 54 pages
File Size : 13,94 MB
Release : 1990
Category : Groundwater
ISBN :
Author : A. Tveito
Publisher : Springer Science & Business Media
Page : 404 pages
File Size : 36,63 MB
Release : 2012-12-06
Category : Mathematics
ISBN : 1461219841
13. 2 Abstract Saddle Point Problems . 282 13. 3 Preconditioned Iterative Methods . 283 13. 4 Examples of Saddle Point Problems 286 13. 5 Discretizations of Saddle Point Problems. 290 13. 6 Numerical Results . . . . . . . . . . . . . 295 III GEOMETRIC MODELLING 299 14 Surface Modelling from Scattered Geological Data 301 N. P. Fremming, @. Hjelle, C. Tarrou 14. 1 Introduction. . . . . . . . . . . 301 14. 2 Description of Geological Data 302 14. 3 Triangulations . . . . . . . . 304 14. 4 Regular Grid Models . . . . . 306 14. 5 A Composite Surface Model. 307 14. 6 Examples . . . . . . 312 14. 7 Concluding Remarks. . . . . 314 15 Varioscale Surfaces in Geographic Information Systems 317 G. Misund 15. 1 Introduction. . . . . . . . . . . . . . . 317 15. 2 Surfaces of Variable Resolution . . . . 318 15. 3 Surface Varioscaling by Normalization 320 15. 4 Examples . . . 323 15. 5 Final Remarks . . . . . . . . . . . . . 327 16 Surface Modelling from Biomedical Data 329 J. G. Bjaalie, M. Dtllhlen, T. V. Stensby 16. 1 Boundary Polygons. . . . . . . . . . . 332 16. 2 Curve Approximation . . . . . . . . . 333 16. 3 Reducing Twist in the Closed Surface 336 16. 4 Surface Approximation. 337 16. 5 Open Surfaces. . . . 339 16. 6 Examples . . . . . . 340 16. 7 Concluding Remarks 344 17 Data Reduction of Piecewise Linear Curves 347 E. Arge, M. Dtllhlen 17. 1 Introduction. . . . . . . . . . . 347 17. 2 Preliminaries . . . . . . . . . . 349 17. 3 The Intersecting Cones Method 351 17. 4 The Improved Douglas Method 353 17. 5 Numerical Examples . . . . . . 360 17. 6 Resolution Sorting . . . . . . . . . . . . . . . . . . 361 18 Aspects of Algorithms for Manifold Intersection 365 T. Dokken 18. 1 Introduction . . . . . . . . . . . . . . . 365 18. 2 Basic Concepts Used . . . . . . . . . .
