
Topological Methods in Data Analysis and Visualization II: Theory, Algorithms, and Applications (Mathematics and Visualization)
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Product Description
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 structuresas found in scalar, vector and tensor fieldshave 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 analysistheory, algorithms and applications.
Book Specifications
| ISBN-13 | 9783642231742 |
| ISBN-10 | 3642231748 |
| Publisher | Springer Nature |
| Language | English |
| Dimensions | 15.75 x 1.78 x 23.88 cm |
| Weight | 544 g |
| Country | Germany |
| Category | Programming & Software Development › Algorithms |
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