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Topological Methods in Data Analysis and Visualization V - Theory, Algorithms, and Applications (Hardcover, 1st ed. 2020):... Topological Methods in Data Analysis and Visualization V - Theory, Algorithms, and Applications (Hardcover, 1st ed. 2020)
Hamish Carr, Issei Fujishiro, Filip Sadlo, Shigeo Takahashi
R4,550 Discovery Miles 45 500 Ships in 12 - 17 working days

This collection of peer-reviewed workshop papers provides comprehensive coverage of cutting-edge research into topological approaches to data analysis and visualization. It encompasses the full range of new algorithms and insights, including fast homology computation, comparative analysis of simplification techniques, and key applications in materials and medical science. The book also addresses core research challenges such as the representation of large and complex datasets, and integrating numerical methods with robust combinatorial algorithms. In keeping with the focus of the TopoInVis 2017 Workshop, the contributions reflect the latest advances in finding experimental solutions to open problems in the sector. They provide an essential snapshot of state-of-the-art research, helping researchers to keep abreast of the latest developments and providing a basis for future work. Gathering papers by some of the world's leading experts on topological techniques, the book represents a valuable contribution to a field of growing importance, with applications in disciplines ranging from engineering to medicine.

Topological Methods in Data Analysis and Visualization V - Theory, Algorithms, and Applications (Paperback, 1st ed. 2020):... Topological Methods in Data Analysis and Visualization V - Theory, Algorithms, and Applications (Paperback, 1st ed. 2020)
Hamish Carr, Issei Fujishiro, Filip Sadlo, Shigeo Takahashi
R5,244 Discovery Miles 52 440 Ships in 10 - 15 working days

This collection of peer-reviewed workshop papers provides comprehensive coverage of cutting-edge research into topological approaches to data analysis and visualization. It encompasses the full range of new algorithms and insights, including fast homology computation, comparative analysis of simplification techniques, and key applications in materials and medical science. The book also addresses core research challenges such as the representation of large and complex datasets, and integrating numerical methods with robust combinatorial algorithms. In keeping with the focus of the TopoInVis 2017 Workshop, the contributions reflect the latest advances in finding experimental solutions to open problems in the sector. They provide an essential snapshot of state-of-the-art research, helping researchers to keep abreast of the latest developments and providing a basis for future work. Gathering papers by some of the world's leading experts on topological techniques, the book represents a valuable contribution to a field of growing importance, with applications in disciplines ranging from engineering to medicine.

Topological Methods in Data Analysis and Visualization II - Theory, Algorithms, and Applications (Hardcover, 2012): Ronald... Topological Methods in Data Analysis and Visualization II - Theory, Algorithms, and Applications (Hardcover, 2012)
Ronald Peikert, Helwig Hauser, Hamish Carr, Raphael Fuchs
R2,992 Discovery Miles 29 920 Out of stock

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.

Topological Methods in Data Analysis and Visualization II - Theory, Algorithms, and Applications (Paperback, Softcover reprint... Topological Methods in Data Analysis and Visualization II - Theory, Algorithms, and Applications (Paperback, Softcover reprint of the original 1st ed. 2012)
Ronald Peikert, Helwig Hauser, Hamish Carr, Raphael Fuchs
R4,041 R3,792 Discovery Miles 37 920 Save R249 (6%) Out of stock

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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