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Topological Methods in Data Analysis and Visualization V: Theory, Algorithms, and Applications: Mathematics and Visualization

Editat de Hamish Carr, Issei Fujishiro, Filip Sadlo, Shigeo Takahashi
en Limba Engleză Paperback – 12 dec 2021
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, thebook represents a valuable contribution to a field of growing importance, with applications in disciplines ranging from engineering to medicine.
 

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Specificații

ISBN-13: 9783030430382
ISBN-10: 3030430383
Ilustrații: X, 270 p. 132 illus., 109 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.4 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Mathematics and Visualization

Locul publicării:Cham, Switzerland

Cuprins

Persistence.- Scalar Topology.- Time-Varying Topology.- Multivariate Topology.- Other Forms of Topology.

Textul de pe ultima copertă

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 bookrepresents a valuable contribution to a field of growing importance, with applications in disciplines ranging from engineering to medicine.


Caracteristici

Covers the full range of cutting-edge research in the sector Features work by the most prominent and respected researchers Addresses key issues such as representing big data Contains papers on the latest developments including fast homology computation