MOMENTAN AUSVERKAUFT
Über dieses Produkt
Product Identifiers
PublisherCambridge University Press
ISBN-101009098160
ISBN-139781009098168
eBay Product ID (ePID)21057258685
Product Key Features
Number of Pages450 Pages
LanguageEnglish
Publication NameComputational Topology for Data Analysis
SubjectGeneral, Topology
Publication Year2022
FeaturesNew Edition
TypeTextbook
Subject AreaMathematics
AuthorYusu Wang, Tamal Krishna Dey
FormatHardcover
Dimensions
Item Height1.2 in
Item Length9.2 in
Item Width6.1 in
Additional Product Features
Intended AudienceCollege Audience
LCCN2021-041859
Reviews'There are many things to appreciate about this book, including the abundance of excellent and helpful figures, the extensive reference list, and the variety of instructive exercises for students to work through ... Thanks to its inclusion of so much cutting-edge recent work and state-of-the-art algorithms, this is an ideal book for mathematicians or computer scientists looking to dive into this exciting and still very young area of research.' Ellen Gasparovic, Mathematical Association of America Reviews, 'A must-have up-to-date computational account of a vibrant area connecting pure mathematics with applications.' Herbert Edelsbrunner, IST Austria
Dewey Edition23
IllustratedYes
Dewey Decimal514.7
Table Of Content1. Basics; 2. Complexes and homology groups; 3. Topological persistence; 4. General persistence; 5. Generators and optimality; 6. Topological analysis of point clouds; 7. Reeb graphs; 8. Topological analysis of graphs; 9. Cover, nerve and Mapper; 10. Discrete Morse theory and applications; 11. Multiparameter persistence and decomposition; 12. Multiparameter persistence and distances; 13. Topological persistence and machine learning.
Edition DescriptionNew Edition
SynopsisTopological data analysis (TDA) has emerged recently as a viable tool for analyzing complex data in applied domains. This comprehensive text covers the current state of the field for students in mathematics and computer science, providing a computational and algorithmic foundation for techniques in TDA., Topological data analysis (TDA) has emerged recently as a viable tool for analyzing complex data, and the area has grown substantially both in its methodologies and applicability. Providing a computational and algorithmic foundation for techniques in TDA, this comprehensive, self-contained text introduces students and researchers in mathematics and computer science to the current state of the field. The book features a description of mathematical objects and constructs behind recent advances, the algorithms involved, computational considerations, as well as examples of topological structures or ideas that can be used in applications. It provides a thorough treatment of persistent homology together with various extensions - like zigzag persistence and multiparameter persistence - and their applications to different types of data, like point clouds, triangulations, or graph data. Other important topics covered include discrete Morse theory, the Mapper structure, optimal generating cycles, as well as recent advances in embedding TDA within machine learning frameworks.
LC Classification NumberQA611.D476 2022
