Topological Methods in Data Analysis and Visualization II: Theory, Algorithms, and Applications - Mathematics and Visualization (Paperback)Ronald Peikert (editor), Helwig Hauser (editor), Hamish Carr (editor), Raphael Fuchs (editor)
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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.
Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Number of pages: 299
Weight: 646 g
Dimensions: 235 x 155 mm
Edition: Softcover reprint of the original 1st ed. 201
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