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＜電子ブック＞
Topological Methods in Data Analysis and Visualization II : Theory, Algorithms, and Applications / edited by Ronald Peikert, Helwig Hauser, Hamish Carr, Raphael Fuchs
(Mathematics and Visualization. ISSN:2197666X)

版	1st ed. 2012.
出版者	(Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer)
出版年	2012
本文言語	英語
大きさ	XI, 299 p. 200 illus., 106 illus. in color : online resource
著者標目	Peikert, Ronald editor Hauser, Helwig editor Carr, Hamish editor Fuchs, Raphael editor SpringerLink (Online service)
件　名	LCSH:Information visualization LCSH:Algorithms LCSH:Artificial intelligence LCSH:Computer graphics FREE:Data and Information Visualization FREE:Algorithms FREE:Artificial Intelligence FREE:Computer Graphics
一般注記	Part I: Discrete Morse Theory.- Part II: Hierarchical Methods for Extracting and Visualizing Topological Structures -- Part III: Visualization of Dynamical Systems, Vector and Tensor Fields -- Part IV: Topological Visualization of Unsteady Flow When scientists analyze datasets in a search for underlying phenomena, patterns or causal factors, their first step is often an automatic or semi-automatic search for structures in the data. Of these feature-extraction methods, topological ones stand out due to their solid mathematical foundation. Topologically defined structures—as found in scalar, vector and tensor fields—have proven their merit in a wide range of scientific domains, and scientists have found them to be revealing in subjects such as physics, engineering, and medicine.   Full of state-of-the-art research and contemporary hot topics in the subject, this volume is a selection of peer-reviewed papers originally presented at the fourth Workshop on Topology-Based Methods in Data Analysis and Visualization, TopoInVis 2011, held in Zurich, Switzerland. The workshop brought together many of the leading lights in the field for a mixture of formal presentations and discussion. One topic currently generating a great deal of interest, and explored in several chapters here, is the search for topological structures in time-dependent flows, and their relationship with Lagrangian coherent structures. Contributors also focus on discrete topologies of scalar and vector fields, and on persistence-based simplification, among other issues of note. The new research results included in this volume relate to all three key areas in data analysis—theory, algorithms and applications HTTP:URL=https://doi.org/10.1007/978-3-642-23175-9

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