Peikert / Fuchs / Hauser | Topological Methods in Data Analysis and Visualization II | Buch | 978-3-662-51906-6 | sack.de

Buch, Englisch, 299 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 532 g

Reihe: Mathematics and Visualization

Peikert / Fuchs / Hauser

Topological Methods in Data Analysis and Visualization II

Theory, Algorithms, and Applications
Softcover Nachdruck of the original 1. Auflage 2012
ISBN: 978-3-662-51906-6
Verlag: Springer

Theory, Algorithms, and Applications

Buch, Englisch, 299 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 532 g

Reihe: Mathematics and Visualization

ISBN: 978-3-662-51906-6
Verlag: Springer


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.

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Zielgruppe


Research

Weitere Infos & Material


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.



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