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Exploiting Hidden Structure in Matrix Computations: Algorithms and Applications : Cetraro, Italy 2015 / by Michele Benzi, Dario Bini, Daniel Kressner, Hans Munthe-Kaas, Charles Van Loan ; edited by Michele Benzi, Valeria Simoncini
(C.I.M.E. Foundation Subseries. ISSN:29461820 ; 2173)
版 | 1st ed. 2016. |
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出版者 | Cham : Springer International Publishing : Imprint: Springer |
出版年 | 2016 |
本文言語 | 英語 |
大きさ | IX, 406 p. 57 illus., 46 illus. in color : online resource |
著者標目 | *Benzi, Michele author Bini, Dario author Kressner, Daniel author Munthe-Kaas, Hans author Van Loan, Charles author Benzi, Michele editor Simoncini, Valeria editor SpringerLink (Online service) |
件 名 | LCSH:Numerical analysis LCSH:Mathematics -- Data processing 全ての件名で検索 FREE:Numerical Analysis FREE:Computational Science and Engineering |
一般注記 | Focusing on special matrices and matrices which are in some sense `near’ to structured matrices, this volume covers a broad range of topics of current interest in numerical linear algebra. Exploitation of these less obvious structural properties can be of great importance in the design of efficient numerical methods, for example algorithms for matrices with low-rank block structure, matrices with decay, and structured tensor computations. Applications range from quantum chemistry to queuing theory. Structured matrices arise frequently in applications. Examples include banded and sparse matrices, Toeplitz-type matrices, and matrices with semi-separable or quasi-separable structure, as well as Hamiltonian and symplectic matrices. The associated literature is enormous, and many efficient algorithms have been developed for solving problems involving such matrices. The text arose from a C.I.M.E. course held in Cetraro (Italy) in June 2015 which aimed to present this fast growing field to young researchers, exploiting the expertise of five leading lecturers with different theoretical and application perspectives HTTP:URL=https://doi.org/10.1007/978-3-319-49887-4 |
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電子ブック | オンライン | 電子ブック |
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Springer eBooks | 9783319498874 |
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EB00236152 |
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データ種別 | 電子ブック |
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分 類 | LCC:QA297-299.4 DC23:518 |
書誌ID | 4000115847 |
ISBN | 9783319498874 |
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