
Overview
- Provides an integrated view of discrepancy theory and its applications
- The various areas of discrepancy theory are bridged with a focus on the state of the art
- Serves as invitation to researchers and students to explore the different methods and to motivate interdisciplinary research
Part of the book series: Lecture Notes in Mathematics (LNM, volume 2107)
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About this book
This is the first work on Discrepancy Theory to show the present variety of points of view and applications covering the areas Classical and Geometric Discrepancy Theory, Combinatorial Discrepancy Theory and Applications and Constructions. It consists of several chapters, written by experts in their respective fields and focusing on the different aspects of the theory.
Discrepancy theory concerns the problem of replacing a continuous object with a discrete sampling and is currently located at the crossroads of number theory, combinatorics, Fourier analysis, algorithms and complexity, probability theory and numerical analysis. This book presents an invitation to researchers and students to explore the different methods and is meant to motivate interdisciplinary research.
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Keywords
Table of contents (10 chapters)
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Classical and Geometric Discrepancy
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Combinatorial Discrepancy
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Applications and Constructions
Editors and Affiliations
Bibliographic Information
Book Title: A Panorama of Discrepancy Theory
Editors: William Chen, Anand Srivastav, Giancarlo Travaglini
Series Title: Lecture Notes in Mathematics
DOI: https://doi.org/10.1007/978-3-319-04696-9
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Softcover ISBN: 978-3-319-04695-2Published: 20 October 2014
eBook ISBN: 978-3-319-04696-9Published: 07 October 2014
Series ISSN: 0075-8434
Series E-ISSN: 1617-9692
Edition Number: 1
Number of Pages: XVI, 695
Number of Illustrations: 29 b/w illustrations
Topics: Number Theory, Combinatorics, Fourier Analysis, Mathematics of Algorithmic Complexity, Probability Theory and Stochastic Processes, Numerical Analysis