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Numerical Methods for Large Eigenvalue Problems (Algorithms and Architectures for Advanced Scientific Computing) - Hardcover

 
9780719033865: Numerical Methods for Large Eigenvalue Problems (Algorithms and Architectures for Advanced Scientific Computing)

Synopsis

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 Each chapter was updated by shortening or deleting outdated topics, adding topics of more recent interest, and adapting the Notes and References section.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

Audience: This book is intended for researchers in applied mathematics and scientific computing as well as for practitioners interested in understanding the theory of numerical methods used for eigenvalue problems. It also can be used as a supplemental text for an advanced graduate-level course on these methods.

Contents: Chapter One: Background in Matrix Theory and Linear Algebra; Chapter Two: Sparse Matrices; Chapter Three: Perturbation Theory and Error Analysis; Chapter Four: The Tools of Spectral Approximation; Chapter Five: Subspace Iteration; Chapter Six: Krylov Subspace Methods; Chapter Seven: Filtering and Restarting Techniques; Chapter Eight: Preconditioning Techniques; Chapter Nine: Non-Standard Eigenvalue Problems; Chapter Ten: Origins of Matrix Eigenvalue Problems

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Book Description

This revised edition discusses numerical methods for computing the eigenvalues and eigenvectors of large sparse matrices. For researchers in applied mathematics and scientific computing, and can also be used as a supplementary text for an advanced graduate course on these methods.

From the Publisher

Offers a timely, in-depth perspective of numerical techniques used in solving large matrix eigenvalue problems arising in diverse engineering and scientific applications. Although important material for symmetric problems is covered, the focus is placed on more difficult nonsymmetric issues. Features solid theoretical treatment-- all of the latest plus well-known methods--and lists of some key computer programs.

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  • PublisherJohn Wiley & Sons
  • Publication date1992
  • ISBN 10 0719033861
  • ISBN 13 9780719033865
  • BindingHardcover
  • LanguageEnglish
  • Number of pages220

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9781611970722: Numerical Methods for Large Eigenvalue Problems (Classics in Applied Mathematics, Series Number 66)

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ISBN 10:  1611970725 ISBN 13:  9781611970722
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ISBN 10: 0719033861 ISBN 13: 9780719033865
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Softcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 65 SAA 9780719033865 Sprache: Englisch Gewicht in Gramm: 450. Seller Inventory # 2497698

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Published by John Wiley & Sons (edition ), 1992
ISBN 10: 0719033861 ISBN 13: 9780719033865
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First Edition. Fine copy in the original paper-covered boards. Slightest suggestion only of dust-dulling to the spine bands and panel edges. Remains particularly well-preserved overall; tight, bright, clean and strong. Physical description: 346 pages : illustrations ; 24 cm. Subject: Nonsymmetric matrices. Eigenvalues. Matrices. 1 Kg. Seller Inventory # 383486

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First Edition. Fine copy in the original paper-covered boards. Slightest suggestion only of dust-dulling to the spine bands and panel edges. Remains particularly well-preserved overall; tight, bright, clean and strong. Physical description: 346 pages : illustrations ; 24 cm. Subject: Nonsymmetric matrices. Eigenvalues. Matrices. 1 Kg. Seller Inventory # 383486

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