Euclidean Distance Geometry: An Introduction - Springer Undergraduate Texts in Mathematics and Technology (Hardback)
  • Euclidean Distance Geometry: An Introduction - Springer Undergraduate Texts in Mathematics and Technology (Hardback)
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Euclidean Distance Geometry: An Introduction - Springer Undergraduate Texts in Mathematics and Technology (Hardback)

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£45.99
Hardback 133 Pages / Published: 12/10/2017
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This textbook, the first of its kind, presents the fundamentals of distance geometry: theory, useful methodologies for obtaining solutions, and real world applications. Concise proofs are given and step-by-step algorithms for solving fundamental problems efficiently and precisely are presented in Mathematica ®, enabling the reader to experiment with concepts and methods as they are introduced. Descriptive graphics, examples, and problems, accompany the real gems of the text, namely the applications in visualization of graphs, localization of sensor networks, protein conformation from distance data, clock synchronization protocols, robotics, and control of unmanned underwater vehicles, to name several. Aimed at intermediate undergraduates, beginning graduate students, researchers, and practitioners, the reader with a basic knowledge of linear algebra will gain an understanding of the basic theories of distance geometry and why they work in real life.

Publisher: Springer International Publishing AG
ISBN: 9783319607917
Number of pages: 133
Weight: 4652 g
Dimensions: 254 x 178 mm
Edition: 1st ed. 2017


MEDIA REVIEWS

"The authors make use of the computing system Mathematica to show step-by step proofs. Aimed at students with a solid foundation in linear algebra, this text would be appropriate for upper-level undergraduates or graduate students." (J. A. Bakal, Choice, Vol. 55 (12), August, 2018)


"This textbook on distance geometry covers some relevant theory with several algorithms presented in Mathematica. ... The featured problems explore graph visualization, sensor networks, molecule topology and more. Beginning graduate students and researchers with a suitable foundation in graph, vector, and matrix theory as well as linear algebra will gain from the modeling explorations here." (Tom Schulte, MAA Reviews, March, 2018)

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