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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Wedi'i Gadw mewn:
Manylion Llyfryddiaeth
Prif Awdur: Peikert, Ronald
Awduron Eraill: Hauser, Helwig (Cyfarwyddwr cyhoeddi), Carr, Hamish (Cyfarwyddwr cyhoeddi), Fuchs, Raphael (Cyfarwyddwr cyhoeddi)
Fformat: Livre numérique
Iaith:Anglais
Cyhoeddwyd: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
Rhifyn:2012.
Cyfres:Mathematics and Visualization
Mynediad Ar-lein:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Nodyn: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Topological Methods in Data Analysis and Visualization II, Texte imprimé, 9783642231742
• Topological Methods in Data Analysis and Visualization II, Texte imprimé, 9783642231766
• Topological Methods in Data Analysis and Visualization II, Texte imprimé, 9783662519066
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245 1 0 |a Topological methods in data analysis and visualization.  |n II,  |p Theory, algorithms, and applications   |c edited by Ronald Peikert, Helwig Hauser, Hamish Carr, Raphael Fuchs. 
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505 1 |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 
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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 Fuchs, Raphael.  |4 pbd 
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