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＜電子ブック＞
Topological Methods in Data Analysis and Visualization V : Theory, Algorithms, and Applications / edited by Hamish Carr, Issei Fujishiro, Filip Sadlo, Shigeo Takahashi
(Mathematics and Visualization. ISSN:2197666X)

版	1st ed. 2020.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2020
本文言語	英語
大きさ	X, 270 p. 132 illus., 109 illus. in color : online resource
著者標目	Carr, Hamish editor Fujishiro, Issei editor Sadlo, Filip editor Takahashi, Shigeo editor SpringerLink (Online service)
件　名	LCSH:Information visualization LCSH:Dynamical systems LCSH:Computer science -- Mathematics  全ての件名で検索 LCSH:Manifolds (Mathematics) LCSH:Geometry FREE:Data and Information Visualization FREE:Dynamical Systems FREE:Mathematical Applications in Computer Science FREE:Manifolds and Cell Complexes FREE:Geometry
一般注記	Persistence -- Scalar Topology -- Time-Varying Topology -- Multivariate Topology -- Other Forms of Topology 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 HTTP:URL=https://doi.org/10.1007/978-3-030-43036-8

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