Bidiagonal Singular Value Decomposition by Percy Deift (5 results)

- Softcover
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

- Softcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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£ 20.77
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

- Hardcover
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

- Hardcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
Contact seller5-star sellerCondition: New
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HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.
More images- Softcover
- Print on Demand
Seller: Forgotten Books, London, United KingdomForgotten Books
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£ 13.82
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Paperback. Condition: New. Print on Demand. This book delves into the complex world of singular value decomposition (SVD), a fundamental mathematical operation used to analyze matrices. It examines the process of computing the SVD of a bidiagonal matrix, a specific type of matrix that arises in various applications, including the SVD of general matrices and the eigenproblem of symmetric tridiagonal matrices. The author's exploration of this topic builds upon existing research in the field, particularly the work of Demmel and Kahan, and presents new insights regarding the accuracy of SVD computations. The book's core theme revolves around demonstrating that SVD calculations on bidiagonal matrices can achieve significantly higher accuracy than those performed on general matrices. This unexpected result stems from the nature of bidiagonal matrices, where relative errors in the entries lead to relative errors in the singular values, unlike in general matrices where absolute errors are dominant. Furthermore, the book introduces a novel Hamiltonian approach to analyze the algorithm used for SVD calculations. This approach, drawing upon the concepts of Hamiltonian mechanics, reveals a deeper understanding of how errors propagate during the computation process. The book's exploration of Hamiltonian mechanics and its application to the SVD algorithm offers a new paradigm for developing high-accuracy algorithms for solving other eigenvalue problems. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item.…