Editors:
- Latest, peer-reviewed results in a growing research area
- Topic with close interaction of mathematics and computer science
- Many applications to science and engineering
- Includes supplementary material: sn.pub/extras
Part of the book series: Mathematics and Visualization (MATHVISUAL)
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Table of contents (19 chapters)
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Front Matter
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Discrete Morse Theory
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Front Matter
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Computational discrete morse theory
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Hierarchical methods for extracting and visualizing topological structures
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Front Matter
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Visualization of dynamical systems, vector and tensor fields
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Front Matter
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Hierarchical methods
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Topological Visualization of unsteady flow
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Front Matter
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About this book
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.
Editors and Affiliations
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Inst. Computational Science, CAB G 65.1, ETH Zürich, Zürich, Switzerland
Ronald Peikert
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, Dept. of Informatics, University of Bergen, Bergen, Norway
Helwig Hauser
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, School of Computing, University of Leeds, Leeds, United Kingdom
Hamish Carr
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, Computational Science, ETH Zürich, Zürich, Switzerland
Raphael Fuchs
Bibliographic Information
Book Title: Topological Methods in Data Analysis and Visualization II
Book Subtitle: Theory, Algorithms, and Applications
Editors: Ronald Peikert, Helwig Hauser, Hamish Carr, Raphael Fuchs
Series Title: Mathematics and Visualization
DOI: https://doi.org/10.1007/978-3-642-23175-9
Publisher: Springer Berlin, Heidelberg
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2012
Hardcover ISBN: 978-3-642-23174-2Published: 25 January 2012
Softcover ISBN: 978-3-662-51906-6Published: 23 August 2016
eBook ISBN: 978-3-642-23175-9Published: 10 January 2012
Series ISSN: 1612-3786
Series E-ISSN: 2197-666X
Edition Number: 1
Number of Pages: XI, 299
Topics: Visualization, Algorithms, Artificial Intelligence, Computer Graphics