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Synopsis
Designed for first-year graduate students from a variety of engineering and scientific disciplines, this comprehensive textbook covers the solution of linear systems, least squares problems, eigenvalue problems, and the singular value decomposition. The author, who helped design the widely used LAPACK and ScaLAPACK linear algebra libraries, draws on this experience to present state-of-the-art techniques for these problems, including recommending which algorithms to use in various practical situations. Algorithms are derived in a mathematically illuminating way, including condition numbers and error bounds. Direct and iterative algorithms, suitable for dense and sparse matrices, are discussed. Algorithm design for modern computer architectures, where moving data is often more expensive than arithmetic operations, is discussed in detail, using LAPACK as an illustration. There are many numerical examples throughout the text and in the problems at the ends of chapters, most of which are written in MATLAB and are freely available on the Web.
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About the Author
James Demmel is a Professor in the Computer Science Division and Mathematics Department at the University of California, Berkeley. He was elected to the National Academy of Engineering in 1999.
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Applied Numerical Linear Algebra
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Applied Numerical Linear Algebra
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Condition: New. This comprehensive textbook is designed for first-year graduate students from a variety of engineering and scientific disciplines. Num Pages: 184 pages, Illustrations. BIC Classification: PBF; PDE; TBJ. Category: (U) Tertiary Education (US: College). Dimension: 171 x 255 x 22. Weight in Grams: 972. 184 pages, Illustrations. This comprehensive textbook is designed for first-year graduate students from a variety of engineering and scientific disciplines. Cateogry: (U) Tertiary Education (US: College). BIC Classification: PBF; PDE; TBJ. Dimension: 171 x 255 x 22. Weight: 966. . 1997. 1st Edition. Paperback. . . . . Seller Inventory # V9780898713893
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