Numerical Methods For General And Structured Eigenvalue Problems
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Author |
: Daniel Kressner |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 272 |
Release |
: 2006-01-20 |
ISBN-10 |
: 9783540285021 |
ISBN-13 |
: 3540285024 |
Rating |
: 4/5 (21 Downloads) |
Synopsis Numerical Methods for General and Structured Eigenvalue Problems by : Daniel Kressner
This book is about computing eigenvalues, eigenvectors, and invariant subspaces of matrices. Treatment includes generalized and structured eigenvalue problems and all vital aspects of eigenvalue computations. A unique feature is the detailed treatment of structured eigenvalue problems, providing insight on accuracy and efficiency gains to be expected from algorithms that take the structure of a matrix into account.
Author |
: Daniel Kressner (Mathématicien) |
Publisher |
: |
Total Pages |
: |
Release |
: 2004 |
ISBN-10 |
: OCLC:177148021 |
ISBN-13 |
: |
Rating |
: 4/5 (21 Downloads) |
Synopsis Numerical Methods and Software for General and Structured Eigenvalue Problems by : Daniel Kressner (Mathématicien)
Author |
: Angelika Bunse-Gerstner |
Publisher |
: |
Total Pages |
: 49 |
Release |
: 1987 |
ISBN-10 |
: OCLC:230968533 |
ISBN-13 |
: |
Rating |
: 4/5 (33 Downloads) |
Synopsis A chart of numerical methods for structured eigenvalue problems by : Angelika Bunse-Gerstner
Author |
: Yousef Saad |
Publisher |
: SIAM |
Total Pages |
: 285 |
Release |
: 2011-05-26 |
ISBN-10 |
: 9781611970722 |
ISBN-13 |
: 1611970725 |
Rating |
: 4/5 (22 Downloads) |
Synopsis Numerical Methods for Large Eigenvalue Problems by : Yousef Saad
This revised edition discusses numerical methods for computing the 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 Each chapter was updated by shortening or deleting outdated topics, adding topics of more recent interest and adapting the Notes and References section.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 |
: Steffen Börm |
Publisher |
: De Gruyter Textbook |
Total Pages |
: 0 |
Release |
: 2012 |
ISBN-10 |
: 3110250330 |
ISBN-13 |
: 9783110250336 |
Rating |
: 4/5 (30 Downloads) |
Synopsis Numerical Methods for Eigenvalue Problems by : Steffen Börm
This textbook presents a number of the most important numerical methods for finding eigenvalues and eigenvectors of matrices. The authors discuss the central ideas underlying the different algorithms and introduce the theoretical concepts required t
Author |
: Moody Chu |
Publisher |
: Oxford University Press |
Total Pages |
: 408 |
Release |
: 2005-06-16 |
ISBN-10 |
: 9780198566649 |
ISBN-13 |
: 0198566646 |
Rating |
: 4/5 (49 Downloads) |
Synopsis Inverse Eigenvalue Problems by : Moody Chu
Inverse eigenvalue problems arise in a remarkable variety of applications and associated with any inverse eigenvalue problem are two fundamental questions--the theoretical issue of solvability and the practical issue of computability. Both questions are difficult and challenging. In this text, the authors discuss the fundamental questions, some known results, many applications, mathematical properties, a variety of numerical techniques, as well as several open problems.This is the first book in the authoritative Numerical Mathematics and Scientific Computation series to cover numerical linear algebra, a broad area of numerical analysis. Authored by two world-renowned researchers, the book is aimed at graduates and researchers in applied mathematics, engineering and computer science and makes an ideal graduate text.
Author |
: Xuefeng Liu |
Publisher |
: Springer Nature |
Total Pages |
: 139 |
Release |
: |
ISBN-10 |
: 9789819735778 |
ISBN-13 |
: 9819735777 |
Rating |
: 4/5 (78 Downloads) |
Synopsis Guaranteed Computational Methods for Self-Adjoint Differential Eigenvalue Problems by : Xuefeng Liu
Author |
: Zhaojun Bai |
Publisher |
: SIAM |
Total Pages |
: 430 |
Release |
: 2000-01-01 |
ISBN-10 |
: 9780898714715 |
ISBN-13 |
: 0898714710 |
Rating |
: 4/5 (15 Downloads) |
Synopsis Templates for the Solution of Algebraic Eigenvalue Problems by : Zhaojun Bai
Mathematics of Computing -- Numerical Analysis.
Author |
: J. Cullum |
Publisher |
: Elsevier |
Total Pages |
: 339 |
Release |
: 1986-01-01 |
ISBN-10 |
: 9780080872384 |
ISBN-13 |
: 0080872387 |
Rating |
: 4/5 (84 Downloads) |
Synopsis Large Scale Eigenvalue Problems by : J. Cullum
Results of research into large scale eigenvalue problems are presented in this volume. The papers fall into four principal categories:novel algorithms for solving large eigenvalue problems, novel computer architectures, computationally-relevant theoretical analyses, and problems where large scale eigenelement computations have provided new insight.
Author |
: Heike Fassbender |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 277 |
Release |
: 2007-05-08 |
ISBN-10 |
: 9780306469787 |
ISBN-13 |
: 0306469782 |
Rating |
: 4/5 (87 Downloads) |
Synopsis Symplectic Methods for the Symplectic Eigenproblem by : Heike Fassbender
The solution of eigenvalue problems is an integral part of many scientific computations. For example, the numerical solution of problems in structural dynamics, electrical networks, macro-economics, quantum chemistry, and c- trol theory often requires solving eigenvalue problems. The coefficient matrix of the eigenvalue problem may be small to medium sized and dense, or large and sparse (containing many zeroelements). In the past tremendous advances have been achieved in the solution methods for symmetric eigenvalue pr- lems. The state of the art for nonsymmetric problems is not so advanced; nonsymmetric eigenvalue problems can be hopelessly difficult to solve in some situations due, for example, to poor conditioning. Good numerical algorithms for nonsymmetric eigenvalue problems also tend to be far more complex than their symmetric counterparts. This book deals with methods for solving a special nonsymmetric eig- value problem; the symplectic eigenvalue problem. The symplectic eigenvalue problem is helpful, e.g., in analyzing a number of different questions that arise in linear control theory for discrete-time systems. Certain quadratic eigenvalue problems arising, e.g., in finite element discretization in structural analysis, in acoustic simulation of poro-elastic materials, or in the elastic deformation of anisotropic materials can also lead to symplectic eigenvalue problems. The problem appears in other applications as well.