Topological Methods in Data Analysis and Visualization

Theory, Algorithms, and Applications
1. Auflage. 2010
ISBN: 978-3-642-15013-5
Verlag: Springer

Buch, Englisch, 260 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 576 g

Reihe: Mathematics and Visualization

Topology-based methods are of increasing importance in the analysis and visualization of datasets from a wide variety of scientific domains such as biology, physics, engineering, and medicine. Current challenges of topology-based techniques include the management of time-dependent data, the representation of large and complex datasets, the characterization of noise and uncertainty, the effective integration of numerical methods with robust combinatorial algorithms, etc.

The editors have brought together the most prominent and best recognized researchers in the field of topology-based data analysis and visualization for a joint discussion and scientific exchange of the latest results in the field.

This book contains the best 20 peer-reviewed papers resulting from the discussions and presentations at the third workshop on "Topological Methods in Data Analysis and Visualization", held 2009 in Snowbird, Utah, US. The 2009 "TopoInVis" workshop follows the two successful workshops in 2005 (Slovakia) and 2007 (Germany).

Zielgruppe

Research

Autoren/Hrsg.

Pascucci, Valerio

Tierny, Julien

Tricoche, Xavier

Hagen, Hans

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen

Inhaltsverzeichnis

Foundations of Computational Topology.- Hierarchical Topological Data-Structures.- Topological Feature Extraction Algorithms.- Applications in Scientific Data Analysis and Visualization.- Topological Analysis of Large-Scale Scientific Data.- Indices.