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Record Nr. |
UNINA9910254062003321 |
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Autore |
Sakata Toshio |
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Titolo |
Algebraic and computational aspects of real tensor ranks [[electronic resource] /] / by Toshio Sakata, Toshio Sumi, Mitsuhiro Miyazaki |
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Pubbl/distr/stampa |
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Tokyo : , : Springer Japan : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (112 p.) |
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Collana |
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JSS Research Series in Statistics, , 2364-0057 |
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Disciplina |
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Soggetti |
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Statistics |
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences |
Statistics and Computing/Statistics Programs |
Statistics for Social Sciences, Humanities, Law |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Basics of Tensor Rank -- 3-Tensors -- Simple Evaluation Methods of Tensor Rank -- Absolutely Nonsingular Tensors and Determinantal Polynomials -- Maximal Ranks -- Typical Ranks -- Global Theory of Tensor Ranks -- 2 × 2 × · · · × 2 Tensors. |
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Sommario/riassunto |
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This book provides comprehensive summaries of theoretical (algebraic) and computational aspects of tensor ranks, maximal ranks, and typical ranks, over the real number field. Although tensor ranks have been often argued in the complex number field, it should be emphasized that this book treats real tensor ranks, which have direct applications in statistics. The book provides several interesting ideas, including determinant polynomials, determinantal ideals, absolutely nonsingular tensors, absolutely full column rank tensors, and their connection to bilinear maps and Hurwitz-Radon numbers. In addition to reviews of methods to determine real tensor ranks in details, global theories such as the Jacobian method are also reviewed in details. The book includes as well an accessible and comprehensive introduction of mathematical backgrounds, with basics of positive polynomials and calculations by using the Groebner basis. Furthermore, this book provides insights into numerical methods of finding tensor ranks through simultaneous singular value decompositions. |
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