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Author: Gerard Meurant
Publisher: SIAM
Published: 2006-08-01
Total Pages: 374
ISBN-13: 0898716160
DOWNLOAD EBOOKThe most comprehensive and up-to-date discussion available of the Lanczos and CG methods for computing eigenvalues and solving linear systems.
Author: Louis Komzsik
Publisher: SIAM
Published: 2003-01-01
Total Pages: 99
ISBN-13: 9780898718188
DOWNLOAD EBOOKThe Lanczos Method: Evolution and Application is divided into two distinct parts. The first part reviews the evolution of one of the most widely used numerical techniques in the industry. The development of the method, as it became more robust, is demonstrated through easy-to-understand algorithms. The second part contains industrial applications drawn from the author's experience. These chapters provide a unique interaction between the numerical algorithms and their engineering applications.
Author: Louis Komzsik
Publisher: SIAM
Published: 2003-01-01
Total Pages: 89
ISBN-13: 0898715377
DOWNLOAD EBOOKA valuable reference on the Lanczos method for graduate numerical analysts and engineers.
Author: James R. Bunch
Publisher: Academic Press
Published: 2014-05-10
Total Pages: 468
ISBN-13: 1483263401
DOWNLOAD EBOOKSparse Matrix Computations is a collection of papers presented at the 1975 Symposium by the same title, held at Argonne National Laboratory. This book is composed of six parts encompassing 27 chapters that contain contributions in several areas of matrix computations and some of the most potential research in numerical linear algebra. The papers are organized into general categories that deal, respectively, with sparse elimination, sparse eigenvalue calculations, optimization, mathematical software for sparse matrix computations, partial differential equations, and applications involving sparse matrix technology. This text presents research on applied numerical analysis but with considerable influence from computer science. In particular, most of the papers deal with the design, analysis, implementation, and application of computer algorithms. Such an emphasis includes the establishment of space and time complexity bounds and to understand the algorithms and the computing environment. This book will prove useful to mathematicians and computer scientists.
Author: Gene H. Golub
Publisher: Princeton University Press
Published: 2009-12-07
Total Pages: 376
ISBN-13: 1400833884
DOWNLOAD EBOOKThis computationally oriented book describes and explains the mathematical relationships among matrices, moments, orthogonal polynomials, quadrature rules, and the Lanczos and conjugate gradient algorithms. The book bridges different mathematical areas to obtain algorithms to estimate bilinear forms involving two vectors and a function of the matrix. The first part of the book provides the necessary mathematical background and explains the theory. The second part describes the applications and gives numerical examples of the algorithms and techniques developed in the first part. Applications addressed in the book include computing elements of functions of matrices; obtaining estimates of the error norm in iterative methods for solving linear systems and computing parameters in least squares and total least squares; and solving ill-posed problems using Tikhonov regularization. This book will interest researchers in numerical linear algebra and matrix computations, as well as scientists and engineers working on problems involving computation of bilinear forms.
Author: Yousef Saad
Publisher: SIAM
Published: 2011-01-01
Total Pages: 292
ISBN-13: 9781611970739
DOWNLOAD EBOOKThis revised edition discusses numerical methods for computing eigenvalues and eigenvectors of large sparse matrices. It provides an in-depth view of the numerical methods that are applicable for solving matrix eigenvalue problems that arise in various engineering and scientific applications. Each chapter was updated by shortening or deleting outdated topics, adding topics of more recent interest, and adapting the Notes and References section. Significant changes have been made to Chapters 6 through 8, which describe algorithms and their implementations and now include topics such as the implicit restart techniques, the Jacobi-Davidson method, and automatic multilevel substructuring.
Author: Yousef Saad
Publisher: SIAM
Published: 2003-04-01
Total Pages: 537
ISBN-13: 0898715342
DOWNLOAD EBOOKMathematics of Computing -- General.
Author: David E. Keyes
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 403
ISBN-13: 9401154120
DOWNLOAD EBOOKIn this volume, designed for computational scientists and engineers working on applications requiring the memories and processing rates of large-scale parallelism, leading algorithmicists survey their own field-defining contributions, together with enough historical and bibliographical perspective to permit working one's way to the frontiers. This book is distinguished from earlier surveys in parallel numerical algorithms by its extension of coverage beyond core linear algebraic methods into tools more directly associated with partial differential and integral equations - though still with an appealing generality - and by its focus on practical medium-granularity parallelism, approachable through traditional programming languages. Several of the authors used their invitation to participate as a chance to stand back and create a unified overview, which nonspecialists will appreciate.
Author: H. A. van der Vorst
Publisher: Cambridge University Press
Published: 2003-04-17
Total Pages: 242
ISBN-13: 9780521818285
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Author: Beresford N. Parlett
Publisher: SIAM
Published: 1998-01-01
Total Pages: 422
ISBN-13: 9781611971163
DOWNLOAD EBOOKAccording to Parlett, "Vibrations are everywhere, and so too are the eigenvalues associated with them. As mathematical models invade more and more disciplines, we can anticipate a demand for eigenvalue calculations in an ever richer variety of contexts." Anyone who performs these calculations will welcome the reprinting of Parlett's book (originally published in 1980). In this unabridged, amended version, Parlett covers aspects of the problem that are not easily found elsewhere. The chapter titles convey the scope of the material succinctly. The aim of the book is to present mathematical knowledge that is needed in order to understand the art of computing eigenvalues of real symmetric matrices, either all of them or only a few. The author explains why the selected information really matters and he is not shy about making judgments. The commentary is lively but the proofs are terse. The first nine chapters are based on a matrix on which it is possible to make similarity transformations explicitly. The only source of error is inexact arithmetic. The last five chapters turn to large sparse matrices and the task of making approximations and judging them.
