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About Topological Methods in Data Analysis and Visualization II: Theory, Algorithms, and Applications
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.
Detailed Information
Author: | Jan Reininghaus, Ingrid Hotz (auth.), Ronald Peikert, Helwig Hauser, Hamish Carr, Raphael Fuchs (eds.) |
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Publication Year: | 2012 |
ISBN: | 9783642231742 |
Pages: | 312 |
Language: | English |
File Size: | 7.21 |
Format: | |
Price: | FREE |
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