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9780470218204
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Numerical Methods for Large Eigenvalue Problems
by Saad, Yousef, and Saad, Youcef, and Saad, Y
1992, Wiley
ISBN-13:
9780470218204
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Add this copy of Numerical Methods for Large Eigenvalue Problems to cart. $29.99, like new condition, Sold by Hypermesh rated 5.0 out of 5 stars, ships from Wilmington, NC, UNITED STATES, published 1992 by Wiley.
Details: ISBN:
0470218207
ISBN-13:
9780470218204
Publisher:
Wiley
Published:
1992
Language:
English
Alibris ID:
17569787796
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Seller's Description: Fine. Personal library, great condition-no writing, highlighting, or bent pages-only difference from "new" is personal library embossing and blacked out library marking on title page. Sewn binding. Cloth over boards. 346 p. Algorithms and Architectures for Advanced Scientific Computi, 3. Audience: General/trade.
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Numerical Methods for Large Eigenvalue Problems / Youcef Saad
by Saad, Youcef
1992, Manchester, UK New York: Manchester University Press; Halsted Press
ISBN-13:
9780470218204
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Add this copy of Numerical Methods for Large Eigenvalue Problems / to cart. $162.00, very good condition, Sold by MW Books rated 5.0 out of 5 stars, ships from Galway, G, IRELAND, published 1992 by Manchester, UK New York: Manchester University Press; Halsted Press.
Edition: 1992, Manchester, UK New York: Manchester University Press; Halsted Press
Hardcover,
Very Good
Details: ISBN:
0470218207
ISBN-13:
9780470218204
Edition:
First Edition
Publisher:
Manchester, UK New York: Manchester University Press; Halsted Press
Published:
1992
Language:
English
Alibris ID:
18812899239
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Seller's Description: Physical description; 346 pages: illustrations; 24 cm. Notes: Includes bibliographical references (pages 323-340) and index. Contents: I. Background in Matrix Theory and Linear Algebra. 1. Matrices. 2. Square Matrices and Eigenvalues. 3. Types of Matrices. 4. Vector Inner Products and Norms. 5. Matrix Norms. 6. Subspaces. 7. Orthogonal Vectors and Subspaces. 8. Canonical Forms of Matrices. 9. Normal and Hermitian Matrices. 10. Nonnegative Matrices--II. Sparse Matrices. 1. Introduction. 2. Storage Schemes. 3. Basic Sparse Matrix Operations. 4. Sparse Direct Solution Methods. 5. Test Problems. 6. SPARSKIT--III. Perturbation Theory and Error Analysis. 1. Projectors and their Properties. 2. A-Posteriori Error Bounds. 3. Conditioning of Eigen-problems. 4. Localization Theorems--IV. The Tools of Spectral Approximation. 1. Single Vector Iterations. 2. Deflation Techniques. 3. General Projection Methods. 4. Chebyshev Polynomials--V. Subspace Iteration. 1. Simple Subspace Iteration. 2. Subspace Iteration with Projection. 3. Practical Implementations--VI. Krylov Subspace Methods. 1. Krylov Subspaces. 2. Arnoldi's Method. 3. The Hermitian Lanczos Algorithm. 4. Non-Hermitian Lanczos Algorithm. 5. Block Krylov Methods. 6. Convergence of the Lanczos Process. 7. Convergence of the Arnoldi Process--VII. Acceleration Techniques and Hybrid Methods. 1. The Basic Chebyshev Iteration. 2. Arnoldi-Chebyshev Iteration. 3. Deflated Arnoldi-Chebyshev. 4. Chebyshev Subspace Iteration. 5. Least Squares--Arnoldi--VIII. Preconditioning Techniques. 1. Shift-and-invert Preconditioning. 2. Polynomial Preconditioning. 3. Davidson's Method. 4. Generalized Arnoldi Algorithms--IX. Non-Standard Eigenvalue Problems. 1. Introduction. 2. Generalized Eigenvalue Problems. 3. Quadratic Problems--X. Origins of Matrix Eigenvalue Problems. 1. Introduction. 2. Mechanical Vibrations. 3. Electrical Networks. 4. Quantum Chemistry. 5. Stability of Dynamical Systems. 6. Bifurcation Analysis. 7. Chemical Reactions. 8. Macro-economics. 9. Markov Chain Models. Subjects: Nonsymmetric matrices. Eigenvalues. Matrices asymétriques. Valeurs propres. Eigenvalues. Nonsymmetric matrices. Valeurs propres. Matrices. Matrices. Near-fine copy in the original illustrated, paper-covered boards. Spine bands and panel edges slightly dulled and dust-toned as with age. Corners sharp with an overall tight, bright and clean impression.
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