applied matrix tensor analysis (21 résultats)

Hardcover. Etat : Good. Etat de la jaquette : No Dust Jacket. 337 pages. Ex-library marks, light wear to the spine and covers; pages toned; a sound binding; good shape. No jacket. Quantity Available: 1. Category: Mathematics; ISBN: 0471234656. ISBN/EAN: 9780471234654. Inventory No: 230552.

paperback. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

Hardcover. Etat : Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides comprehensive reviews of recent progress in matrix variate and tensor variate data analysis from applied points of view. Matrix and tensor approaches for data analysis are known to be extremely useful for recently emerging complex and high-dimensional data in various applied fields. The reviews contained herein cover recent applications of these methods in psychology (Chap. 1), audio signals (Chap. 2) , image analysis from tensor principal component analysis (Chap. 3), and image analysis from decomposition (Chap. 4), and genetic data (Chap. 5) . Readers will be able to understand the present status of these techniques as applicable to their own fields. In Chapter 5 especially, a theory of tensor normal distributions, which is a basic in statistical inference, is developed, and multi-way regression, classification, clustering, and principal component analysis are exemplified under tensor normal distributions. Chapter 6 treats one-sided tests under matrix variate andtensor variate normal distributions, whose theory under multivariate normal distributions has been a popular topic in statistics since the books of Barlow et al. (1972) and Robertson et al. (1988). Chapters 1, 5, and 6 distinguish this book from ordinary engineering books on these topics.

Taschenbuch. Etat : Neu. Applied Matrix and Tensor Variate Data Analysis | Toshio Sakata | Taschenbuch | SpringerBriefs in Statistics | xi | Englisch | 2016 | Springer | EAN 9784431553861 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Hardcover. Etat : Fine condition. Etat de la jaquette : Very Good+ dust jacket. First Printing of the First Edition. New York: Wiley-Interscience / John Wiley & Sons, Inc., 1970. A square, tight copy. Sharp corners. No owner's name or bookplate. No remainder mark. Dust Jacket has 1 very tiny closed tear (less than 1/4 inch). Pages are clean and unmarked. No underlining. No highlighting. No margin notes. Bibliography. Index. First printing, with complete number row (10 987654321) on the copyright page. Bound in the original brown-mustard cloth, lettered in red and light gray on the spine. Includes discussion of Einstein's general relativity, Maxwell's equations, Lorentz transformations, Pauli's spin matrices, Dirac's relativistic wave equation. From the Dust Jacket: "Divided into three parts, the book begins with a thorough development of the direct algebra and octic symmetry of matrices. The second part develops basic concepts of vector and tensor analysis. Aspects of vector analysis discussed include reciprocal lattices, curvilinear coordinate systems, transformations, covariance and contravariance. For tensor analysis, topics cover rank, dimensionality, transformations, quadratic forms, and diagonalization. The last section of the book treats applications to relativity, quantum mechanics, and elementary particle physics." . First Printing of the First Edition. Hard Cover. Fine condition/Very Good+ dust jacket. 8vo. xi, 337pp.

Etat : Gut. Zustand: Gut | Seiten: 350 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Etat : gut. 1970. Applied Matrix and Tensor Analysis. In deutscher Sprache. pages.

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides comprehensive reviews of recent progress in matrix variate and tensor variate data analysis from applied points of view. Matrix and tensor approaches for data analysis are known to be extremely useful for recently emerging complex and high-dimensional data in various applied fields. The reviews contained herein cover recent applications of these methods in psychology (Chap. 1), audio signals (Chap. 2) , image analysis from tensor principal component analysis (Chap. 3), and image analysis from decomposition (Chap. 4), and genetic data (Chap. 5) . Readers will be able to understand the present status of these techniques as applicable to their own fields. In Chapter 5 especially, a theory of tensor normal distributions, which is a basic in statistical inference, is developed, and multi-way regression, classification, clustering, and principal component analysis are exemplified under tensor normal distributions. Chapter 6 treats one-sided tests under matrix variate and tensor variate normal distributions, whose theory under multivariate normal distributions has been a popular topic in statistics since the books of Barlow et al. (1972) and Robertson et al. (1988). Chapters 1, 5, and 6 distinguish this book from ordinary engineering books on these topics. 148 pp. Englisch.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Reviews applications of matrix and tensor variate data analysis by world-leading researchers in several representative applied fields including, psychology, audio signals, image data and geneticsTreats the most important concepts of tensor princip.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides comprehensive reviews of recent progress in matrix variate and tensor variate data analysis from applied points of view. Matrix and tensor approaches for data analysis are known to be extremely useful for recently emerging complex and high-dimensional data in various applied fields. The reviews contained herein cover recent applications of these methods in psychology (Chap. 1), audio signals (Chap. 2) , image analysis from tensor principal component analysis (Chap. 3), and image analysis from decomposition (Chap. 4), and genetic data (Chap. 5) . Readers will be able to understand the present status of these techniques as applicable to their own fields. In Chapter 5 especially, a theory of tensor normal distributions, which is a basic in statistical inference, is developed, and multi-way regression, classification, clustering, and principal component analysis are exemplified under tensor normal distributions. Chapter 6 treats one-sided tests under matrix variate andtensor variate normal distributions, whose theory under multivariate normal distributions has been a popular topic in statistics since the books of Barlow et al. (1972) and Robertson et al. (1988). Chapters 1, 5, and 6 distinguish this book from ordinary engineering books on these topics.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 148 pp. Englisch.