Matrix Computations
Author : Gene Howard Golub
Publisher :
Page : 476 pages
File Size : 17,61 MB
Release : 1983
Category : Matrices
ISBN : 9780946536054
Matrix Computations
Author : Gene Howard Golub
Publisher :
Page : 694 pages
File Size : 39,50 MB
Release : 1983
Category : Matrices
ISBN :
Book Description
Matrix Computations
Author : Gene Howard Golub
Publisher :
Page : 476 pages
File Size : 24,26 MB
Release : 1983
Category : Matrices
ISBN : 9780801830112
Book Description
Matrix Computations
Author : Gene H. Golub
Publisher : JHU Press
Page : 734 pages
File Size : 44,81 MB
Release : 1996-10-15
Category : Mathematics
ISBN : 9780801854149
Book Description
Revised and updated, the third edition of Golub and Van Loan's classic text in computer science provides essential information about the mathematical background and algorithmic skills required for the production of numerical software. This new edition includes thoroughly revised chapters on matrix multiplication problems and parallel matrix computations, expanded treatment of CS decomposition, an updated overview of floating point arithmetic, a more accurate rendition of the modified Gram-Schmidt process, and new material devoted to GMRES, QMR, and other methods designed to handle the sparse unsymmetric linear system problem.
Handbook for Matrix Computations
Author : Thomas F. Coleman
Publisher : SIAM
Page : 271 pages
File Size : 34,16 MB
Release : 1988-01-01
Category : Mathematics
ISBN : 9781611971040
Book Description
Provides the user with a step-by-step introduction to Fortran 77, BLAS, LINPACK, and MATLAB. It is a reference that spans several levels of practical matrix computations with a strong emphasis on examples and "hands on" experience.
Numerical Methods in Matrix Computations
Author : Åke Björck
Publisher : Springer
Page : 812 pages
File Size : 47,18 MB
Release : 2014-10-07
Category : Mathematics
ISBN : 3319050893
Book Description
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.
Parallel Algorithms for Matrix Computations
Author : K. Gallivan
Publisher : SIAM
Page : 207 pages
File Size : 36,59 MB
Release : 1990-01-01
Category : Mathematics
ISBN : 9781611971705
Book Description
Describes a selection of important parallel algorithms for matrix computations. Reviews the current status and provides an overall perspective of parallel algorithms for solving problems arising in the major areas of numerical linear algebra, including (1) direct solution of dense, structured, or sparse linear systems, (2) dense or structured least squares computations, (3) dense or structured eigenvaluen and singular value computations, and (4) rapid elliptic solvers. The book emphasizes computational primitives whose efficient execution on parallel and vector computers is essential to obtain high performance algorithms. Consists of two comprehensive survey papers on important parallel algorithms for solving problems arising in the major areas of numerical linear algebra--direct solution of linear systems, least squares computations, eigenvalue and singular value computations, and rapid elliptic solvers, plus an extensive up-to-date bibliography (2,000 items) on related research.
Matrix Computations
Author : Gene H. Golub
Publisher : JHU Press
Page : 781 pages
File Size : 49,46 MB
Release : 2013-02-15
Category : Mathematics
ISBN : 1421407949
Book Description
This revised edition provides the mathematical background and algorithmic skills required for the production of numerical software. It includes rewritten and clarified proofs and derivations, as well as new topics such as Arnoldi iteration, and domain decomposition methods.
Matrix Computations and Semiseparable Matrices
Author : Raf Vandebril
Publisher : JHU Press
Page : 594 pages
File Size : 15,51 MB
Release : 2008-01-14
Category : Mathematics
ISBN : 0801896797
Book Description
In recent years several new classes of matrices have been discovered and their structure exploited to design fast and accurate algorithms. In this new reference work, Raf Vandebril, Marc Van Barel, and Nicola Mastronardi present the first comprehensive overview of the mathematical and numerical properties of the family's newest member: semiseparable matrices. The text is divided into three parts. The first provides some historical background and introduces concepts and definitions concerning structured rank matrices. The second offers some traditional methods for solving systems of equations involving the basic subclasses of these matrices. The third section discusses structured rank matrices in a broader context, presents algorithms for solving higher-order structured rank matrices, and examines hybrid variants such as block quasiseparable matrices. An accessible case study clearly demonstrates the general topic of each new concept discussed. Many of the routines featured are implemented in Matlab and can be downloaded from the Web for further exploration.
Matrix Algebra
Author : James E. Gentle
Publisher : Springer Science & Business Media
Page : 536 pages
File Size : 43,54 MB
Release : 2007-07-27
Category : Computers
ISBN : 0387708723
Book Description
Matrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory. This much-needed work presents the relevant aspects of the theory of matrix algebra for applications in statistics. It moves on to consider the various types of matrices encountered in statistics, such as projection matrices and positive definite matrices, and describes the special properties of those matrices. Finally, it covers numerical linear algebra, beginning with a discussion of the basics of numerical computations, and following up with accurate and efficient algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors.
