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Euclidean Design Theory, Masanori Sawa; Masatake Hirao; Sanpei Kageyama


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Автор: Masanori Sawa; Masatake Hirao; Sanpei Kageyama
Название:  Euclidean Design Theory
ISBN: 9789811380747
Издательство: Springer
Классификация:


ISBN-10: 9811380740
Обложка/Формат: Soft cover
Страницы: 134
Вес: 0.23 кг.
Дата издания: 2019
Серия: JSS Research Series in Statistics
Язык: English
Издание: 1st ed. 2019
Иллюстрации: 12 illustrations, color; 1 illustrations, black and white; viii, 134 p. 13 illus., 12 illus. in color.
Размер: 234 x 156 x 8
Читательская аудитория: Professional & vocational
Основная тема: Statistics
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: This book is the modern first treatment of experimental designs, providing a comprehensive introduction to the interrelationship between the theory of optimal designs and the theory of cubature formulas in numerical analysis. It also offers original new ideas for constructing optimal designs. The book opens with some basics on reproducing kernels, and builds up to more advanced topics, including bounds for the number of cubature formula points, equivalence theorems for statistical optimalities, and the Sobolev Theorem for the cubature formula. It concludes with a functional analytic generalization of the above classical results. Although it is intended for readers who are interested in recent advances in the construction theory of optimal experimental designs, the book is also useful for researchers seeking rich interactions between optimal experimental designs and various mathematical subjects such as spherical designs in combinatorics and cubature formulas in numerical analysis, both closely related to embeddings of classical finite-dimensional Banach spaces in functional analysis and Hilbert identities in elementary number theory. Moreover, it provides a novel communication platform for “design theorists” in a wide variety of research fields.
Дополнительное описание:
Chapter I: Reproducing Kernel Hilbert Space.- Chapter II: Cubature Formula.- Chapter III: Optimal Euclidean Design.- Chapter IV: Constructions of Optimal Euclidean Design.- Chapter V: Euclidean Design Theory.



Euclidean Distance Matrices and Their Applications in Rigidity Theory

Автор: Abdo Y. Alfakih
Название: Euclidean Distance Matrices and Their Applications in Rigidity Theory
ISBN: 303007417X ISBN-13(EAN): 9783030074173
Издательство: Springer
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Цена: 83850.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a comprehensive and accessible exposition of Euclidean Distance Matrices (EDMs) and rigidity theory of bar-and-joint frameworks. It is based on the one-to-one correspondence between EDMs and projected Gram matrices. Accordingly the machinery of semidefinite programming is a common thread that runs throughout the book. As a result, two parallel approaches to rigidity theory are presented. The first is traditional and more intuitive approach that is based on a vector representation of point configuration. The second is based on a Gram matrix representation of point configuration.

Euclidean Distance Matrices and Their Applications in Rigidity Theory begins by establishing the necessary background needed for the rest of the book. The focus of Chapter 1 is on pertinent results from matrix theory, graph theory and convexity theory, while Chapter 2 is devoted to positive semidefinite (PSD) matrices due to the key role these matrices play in our approach. Chapters 3 to 7 provide detailed studies of EDMs, and in particular their various characterizations, classes, eigenvalues and geometry. Chapter 8 serves as a transitional chapter between EDMs and rigidity theory. Chapters 9 and 10 cover local and universal rigidities of bar-and-joint frameworks. This book is self-contained and should be accessible to a wide audience including students and researchers in statistics, operations research, computational biochemistry, engineering, computer science and mathematics.

Euclidean Distance Matrices and Their Applications in Rigidity Theory

Автор: Abdo Y. Alfakih
Название: Euclidean Distance Matrices and Their Applications in Rigidity Theory
ISBN: 3319978454 ISBN-13(EAN): 9783319978451
Издательство: Springer
Рейтинг:
Цена: 83850.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a comprehensive and accessible exposition of Euclidean Distance Matrices (EDMs) and rigidity theory of bar-and-joint frameworks. It is based on the one-to-one correspondence between EDMs and projected Gram matrices. Accordingly the machinery of semidefinite programming is a common thread that runs throughout the book. As a result, two parallel approaches to rigidity theory are presented. The first is traditional and more intuitive approach that is based on a vector representation of point configuration. The second is based on a Gram matrix representation of point configuration.

Euclidean Distance Matrices and Their Applications in Rigidity Theory begins by establishing the necessary background needed for the rest of the book. The focus of Chapter 1 is on pertinent results from matrix theory, graph theory and convexity theory, while Chapter 2 is devoted to positive semidefinite (PSD) matrices due to the key role these matrices play in our approach. Chapters 3 to 7 provide detailed studies of EDMs, and in particular their various characterizations, classes, eigenvalues and geometry. Chapter 8 serves as a transitional chapter between EDMs and rigidity theory. Chapters 9 and 10 cover local and universal rigidities of bar-and-joint frameworks. This book is self-contained and should be accessible to a wide audience including students and researchers in statistics, operations research, computational biochemistry, engineering, computer science and mathematics.

Introduction to the theory of optimization in euclidean space

Автор: Challal, Samia
Название: Introduction to the theory of optimization in euclidean space
ISBN: 0367195577 ISBN-13(EAN): 9780367195571
Издательство: Taylor&Francis
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Цена: 117390.00 T
Наличие на складе: Невозможна поставка.
Описание: Introduction to the Theory of Optimization in Euclidean Space is intended to provide students with a robust introduction to optimization in Euclidean space, demonstrating the theoretical aspects of the subject whilst also providing clear proofs and applications.


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