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Euclidean Distance Matrices And Their Applications In Rigidity Theory 1st Ed Abdo Y Alfakih

  • SKU: BELL-7324780
Euclidean Distance Matrices And Their Applications In Rigidity Theory 1st Ed Abdo Y Alfakih
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Euclidean Distance Matrices And Their Applications In Rigidity Theory 1st Ed Abdo Y Alfakih instant download after payment.

Publisher: Springer International Publishing
File Extension: PDF
File size: 3.01 MB
Author: Abdo Y. Alfakih
ISBN: 9783319978451, 9783319978468, 3319978454, 3319978462
Language: English
Year: 2018
Edition: 1st ed.

Product desciption

Euclidean Distance Matrices And Their Applications In Rigidity Theory 1st Ed Abdo Y Alfakih by Abdo Y. Alfakih 9783319978451, 9783319978468, 3319978454, 3319978462 instant download after payment.

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.

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