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. T...

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Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Peikert, Ronald (Επιμελητής έκδοσης), Hauser, Helwig (Επιμελητής έκδοσης), Carr, Hamish (Επιμελητής έκδοσης), Fuchs, Raphael (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2012.
Σειρά:Mathematics and Visualization,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Topological Methods in Data Analysis and Visualization II  |h [electronic resource] :  |b Theory, Algorithms, and Applications /  |c edited by Ronald Peikert, Helwig Hauser, Hamish Carr, Raphael Fuchs. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg,  |c 2012. 
300 |a XI, 299 p. 200 illus., 106 illus. in color.  |b online resource. 
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505 0 |a 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. 
520 |a 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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700 1 |a Peikert, Ronald.  |e editor. 
700 1 |a Hauser, Helwig.  |e editor. 
700 1 |a Carr, Hamish.  |e editor. 
700 1 |a Fuchs, Raphael.  |e editor. 
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