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Topological Methods in Data Analysis and Visualization II Theory, Algorithms, and Applications

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 							Ronald Peikert, Helwig Hauser, Hamish Carr, Raphael Fuchs, "Topological Methods in Data Analysis and
Visualization II: Theory, Algorithms, and Applications"
  English | 2012 | 310 Pages | ISBN: 3642231748 | PDF | 7
MB
  
  
  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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