Topological Methods in Data Analysis and Visualization V - Theory, Algorithms, and Applications (Hardcover, 1st ed. 2020)

This collection of peer-reviewed workshop papers provides comprehensive coverage of cutting-edge research into topological approaches to data analysis and visualization. It encompasses the full range of new algorithms and insights, including fast homology computation, comparative analysis of simplification techniques, and key applications in materials and medical science. The book also addresses core research challenges such as the representation of large and complex datasets, and integrating numerical methods with robust combinatorial algorithms. In keeping with the focus of the TopoInVis 2017 Workshop, the contributions reflect the latest advances in finding experimental solutions to open problems in the sector. They provide an essential snapshot of state-of-the-art research, helping researchers to keep abreast of the latest developments and providing a basis for future work. Gathering papers by some of the world's leading experts on topological techniques, the book represents a valuable contribution to a field of growing importance, with applications in disciplines ranging from engineering to medicine.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Mathematics and Visualization
Release date:	December 2020
First published:	2020
Editors:	Hamish Carr • Issei Fujishiro • Filip Sadlo • Shigeo Takahashi
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	270
Edition:	1st ed. 2020
ISBN-13:	978-3-03-043035-1
Categories:	Books > Science & Mathematics > Mathematics > Combinatorics & graph theory Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Science & Mathematics > Mathematics > Geometry > Analytic geometry Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Science & Mathematics > Mathematics > Applied mathematics > Non-linear science Promotions
LSN:	3-03-043035-9
Barcode:	9783030430351

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