| 書目名稱 | Exploiting Hidden Structure in Matrix Computations: Algorithms and Applications | | 副標(biāo)題 | Cetraro, Italy 2015 | | 編輯 | Michele Benzi,Dario Bini,Charles Van Loan,Michele | | 視頻video | http://file.papertrans.cn/320/319376/319376.mp4 | | 概述 | Provides a detailed treatment of the emerging field of hidden or approximate-structured matrix problems.Offers different theoretical and application perspectives in a thorough presentation by leading | | 叢書名稱 | Lecture Notes in Mathematics | | 圖書封面 |  | | 描述 | .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.. | | 出版日期 | Book 2016 | | 關(guān)鍵詞 | Structured matrices; Pattern and decay properties; Structure preserving algorithms; Low rank tensor app | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-49887-4 | | isbn_softcover | 978-3-319-49886-7 | | isbn_ebook | 978-3-319-49887-4Series ISSN 0075-8434 Series E-ISSN 1617-9692 | | issn_series | 0075-8434 | | copyright | Springer International Publishing AG 2016 |
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