Large Scale Eigenvalue Problems

Large Scale Eigenvalue Problems
Author: J. Cullum
Publisher: Elsevier
Total Pages: 339
Release: 1986-01-01
Genre: Mathematics
ISBN: 0080872387

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.

ARPACK Users' Guide

ARPACK Users' Guide
Author: Richard B. Lehoucq
Publisher: SIAM
Total Pages: 150
Release: 1998-01-01
Genre: Mathematics
ISBN: 0898714079

This book is a guide to understanding and using the software package ARPACK to solve large algebraic eigenvalue problems. The software described is based on the implicitly restarted Arnoldi method, which has been heralded as one of the three most important advances in large scale eigenanalysis in the past ten years. The book explains the acquisition, installation, capabilities, and detailed use of the software for computing a desired subset of the eigenvalues and eigenvectors of large (sparse) standard or generalized eigenproblems. It also discusses the underlying theory and algorithmic background at a level that is accessible to the general practitioner.

Numerical Methods for Large Eigenvalue Problems

Numerical Methods for Large Eigenvalue Problems
Author: Yousef Saad
Publisher: SIAM
Total Pages: 292
Release: 2011-01-01
Genre: Mathematics
ISBN: 9781611970739

This 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 Each chapter was updated by shortening or deleting outdated topics, adding topics of more recent interest, and adapting the Notes and References section.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.

Numerical Methods for General and Structured Eigenvalue Problems

Numerical Methods for General and Structured Eigenvalue Problems
Author: Daniel Kressner
Publisher: Springer Science & Business Media
Total Pages: 272
Release: 2006-01-20
Genre: Mathematics
ISBN: 3540285024

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.

Eigenvalue Problems in Power Systems

Eigenvalue Problems in Power Systems
Author: Federico Milano
Publisher: CRC Press
Total Pages: 407
Release: 2020-12-22
Genre: Technology & Engineering
ISBN: 1000335208

The book provides a comprehensive taxonomy of non-symmetrical eigenvalues problems as applied to power systems. The book bases all formulations on mathematical concept of “matrix pencils” (MPs) and considers both regular and singular MPs for the eigenvalue problems. Each eigenvalue problem is illustrated with a variety of examples based on electrical circuits and/or power system models and controllers and related data are provided in the appendices of the book. Numerical methods for the solution of all considered eigenvalue problems are discussed. The focus is on large scale problems and, hence, attention is dedicated to the performance and scalability of the methods. The target of the book are researchers and graduated students in Electrical & Computer Science Engineering, both taught and research Master programmes as well as PhD programmes and it: explains eigenvalue problems applied into electrical power systems explains numerical examples on applying the mathematical methods, into studying small signal stability problems of realistic and large electrical power systems includes detailed and in-depth analysis including non-linear and other advanced aspects provides theoretical understanding and advanced numerical techniques essential for secure operation of power systems provides a comprehensive set of illustrative examples that support theoretical discussions

Parallel Numerical Algorithms

Parallel Numerical Algorithms
Author: David E. Keyes
Publisher: Springer Science & Business Media
Total Pages: 403
Release: 2012-12-06
Genre: Mathematics
ISBN: 9401154120

In 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.

Templates for the Solution of Algebraic Eigenvalue Problems

Templates for the Solution of Algebraic Eigenvalue Problems
Author: Zhaojun Bai
Publisher: SIAM
Total Pages: 439
Release: 2000-01-01
Genre: Computers
ISBN: 9780898719581

Large-scale problems of engineering and scientific computing often require solutions of eigenvalue and related problems. This book gives a unified overview of theory, algorithms, and practical software for eigenvalue problems. It organizes this large body of material to make it accessible for the first time to the many nonexpert users who need to choose the best state-of-the-art algorithms and software for their problems. Using an informal decision tree, just enough theory is introduced to identify the relevant mathematical structure that determines the best algorithm for each problem.