Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 126,38
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New.
Da: Revaluation Books, Exeter, Regno Unito
EUR 180,77
Quantità: 2 disponibili
Aggiungi al carrelloHardcover. Condizione: Brand New. 262 pages. 9.25x6.10x0.71 inches. In Stock.
EUR 136,10
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The book provides an introduction of very recent results about the tensors and mainly focuses on the authors' work and perspective. A systematic description about how to extend the numerical linear algebra to the numerical multi-linear algebra is also delivered in this book. The authors design the neural network model for the computation of the rank-one approximation of real tensors, a normalization algorithm to convert some nonnegative tensors to plane stochastic tensors and a probabilistic algorithm for locating a positive diagonal in a nonnegative tensors,adaptive randomized algorithms for computing the approximate tensor decompositions, andthe QR type method for computing U-eigenpairs of complex tensors.This book could be used for the Graduate course, such as Introduction to Tensor. Researchers may also find it helpful as a reference in tensor research.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 102,25
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer Nature Singapore Apr 2020, 2020
ISBN 10: 9811520585 ISBN 13: 9789811520587
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 128,39
Quantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book provides an introduction of very recent results about the tensors and mainly focuses on the authors' work and perspective. A systematic description about how to extend the numerical linear algebra to the numerical multi-linear algebra is also delivered in this book. The authors design the neural network model for the computation of the rank-one approximation of real tensors, a normalization algorithm to convert some nonnegative tensors to plane stochastic tensors and a probabilistic algorithm for locating a positive diagonal in a nonnegative tensors,adaptive randomized algorithms for computing the approximate tensor decompositions, andthe QR type method for computing U-eigenpairs of complex tensors.This book could be used for the Graduate course, such as Introduction to Tensor. Researchers may also find it helpful as a reference in tensor research. 264 pp. Englisch.
Da: moluna, Greven, Germania
EUR 109,83
Quantità: Più di 20 disponibili
Aggiungi al carrelloGebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces the neural network models and Takagi factorization for the computation of tensor rank-one approximations and US- (U-) eigenvaluesEnriches the properties of nonnegative tensors, defines the sign nonsingular tensors and derives .
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 156,35
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.
Da: Majestic Books, Hounslow, Regno Unito
EUR 168,39
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. Print on Demand.
Lingua: Inglese
Editore: Springer, Springer Apr 2020, 2020
ISBN 10: 9811520585 ISBN 13: 9789811520587
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 128,39
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book provides an introduction of very recent results about the tensors and mainly focuses on the authors' work and perspective. A systematic description about how to extend the numerical linear algebra to the numerical multi-linear algebra is also delivered in this book. The authors design the neural network model for the computation of the rank-one approximation of real tensors, a normalization algorithm to convert some nonnegative tensors to plane stochastic tensors and a probabilistic algorithm for locating a positive diagonal in a nonnegative tensors, adaptive randomized algorithms for computing the approximate tensor decompositions, and the QR type method for computing U-eigenpairs of complex tensors.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 264 pp. Englisch.