Recent advances in iterative methods
著者
書誌事項
Recent advances in iterative methods
（The IMA volumes in mathematics and its applications, v. 60）
Springer-Verlag, c1994
- : us
- : gw
大学図書館所蔵 件 / 全27件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Papers from the IMA Workshop on Iterative Methods for Sparse and Structured Problems, held in Minneapolis, Minn., Feb. 24-Mar. 1, 1992
"Proceedings of a workshop that was an integral part of the 1991-92 IMA program on "Applied Linear Algebra"" -- Foreword
Includes bibliographical references
内容説明・目次
- 巻冊次
-
: us ISBN 9780387942520
内容説明
This IMA Volume in Mathematics and its Applications RECENT ADVANCES IN ITERATIVE METHODS is based on the proceedings of a workshop that was an integral part of the 1991-92 IMA program on "Applied Linear Algebra. " Large systems of matrix equations arise frequently in applications and they have the prop- erty that they are sparse and/or structured. The purpose of this workshop was to bring together researchers in numerical analysis and various ap- plication areas to discuss where such problems arise and possible meth- ods of solution. The last two days of the meeting were a celebration dedicated to Gene Golub on the occasion of his sixtieth birthday, with the program arranged by Jack Dongarra and Paul van Dooren. We are grateful to Richard Brualdi, George Cybenko, Alan George, Gene Golub, Mitchell Luskin, and Paul Van Dooren for planning and implementing the year-long program. We especially thank Gene Golub, Anne Greenbaum, and Mitchell Luskin for organizing this workshop and editing the proceed- ings. The financial support of the National Science Foundation and the Min- nesota Supercomputer Institute made the workshop possible. A vner Friedman Willard Miller, Jr. xi PREFACE The solution of very large linear algebra problems is an integral part of many scientific computations.
目次
Some Themes in Gene H. Golub's Work on Iterative Methods.- Computing the Sparse Singular Value Decomposition via SVDPACK.- Gaussian Quadrature Applied to Adaptive Chebyshev Iteration.- Ordering Effects on Relaxation Methods Applied to the Discrete Convection-Diffusion Equation.- On the Error Computation for Polynomial Based Iteration Methods.- Transpose-Free Quasi-Minimal Residual Methods for non-Hermitian Linear Systems.- Matrices that Generate the Same Krylov Residual Spaces.- Incomplete Block Factorizations as Preconditioners for Sparse SPD Matrices.- How Fast Can Iterative Methods Be?.- Rational Krylov Algorithms for Nonsymmetric Eigenvalue Problems.- Highly Parallel Preconditioners for General Sparse Matrices.- A Two-Stage Iteration for Solving Nearly Completely Decomposable Markov Chains.- Minimum Residual Modifications to Bi-CG and to the Preconditioner.
- 巻冊次
-
: gw ISBN 9783540942528
内容説明
The solution of very large sparse or structured linear algebra problems is an integral part of many scientific computations. Direct methods for solving such problems are often difficult because of computation time and memory requirements, and so iterative techniques are used instead. In recent years, much research has focused on the efficient solution of large systems of linear equations, least squares problems, and eigenvalue problems using iterative methods. This volume on iterative methods for sparse and structured problems brings together researchers to discuss topics of current research. Areas addressed include the development of efficient iterative techniques for solving nonsymmetric linear systems and eigenvalue problems, estimating the convergence rate of such algorithms, and constructing efficient preconditioners for special classes of matrices such as Toeplitz and Hankel matrices. Iteration strategies and preconditioners that could exploit parallelism are of special interest.
「Nielsen BookData」 より
