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

Editat de Ronald Peikert, Helwig Hauser, Hamish Carr, Raphael Fuchs
en Limba Engleză Hardback – 25 ian 2012
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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Specificații

ISBN-13: 9783642231742
ISBN-10: 3642231748
Pagini: 270
Ilustrații: XI, 299 p.
Dimensiuni: 155 x 235 x 15 mm
Greutate: 0.56 kg
Ediția:2012
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Mathematics and Visualization

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

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.

Textul de pe ultima copertă

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.

Caracteristici

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