Authors:
- Excellent introduction to the field
- Suited for the non-specialist
- Very successful book now in a completely revised new edition
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Series in Information Sciences (SSINF, volume 7)
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Table of contents (30 chapters)
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Front Matter
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A Few Fundamentals
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Some Simple Applications
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Congruences and the Like
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Residues and Diffraction
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Chinese and Other Fast Algorithms
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Pseudoprimes, Möbius Transform, and Partitions
About this book
Reviews
From reviews of an earlier editions –
"I continue to find [Schroeder’s] Number Theory a goldmine of valuable information. It is a marvellous book, in touch with the most recent applications of number theory and written with great clarity and humor.’ Philip Morrison (Scientific American)
"A light-hearted and readable volume with a wide range of applications to which the author has been a productive contributor – useful mathematics outside the formalities of theorem and proof." Martin Gardner
Authors and Affiliations
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Drittes Physikalisches Institut, Universität Göttingen, Göttingen, Germany
Manfred R. Schroeder
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Bell Laboratories, Acoustics Speech and Mechanics Research, Murray Hill, USA
Manfred R. Schroeder
Bibliographic Information
Book Title: Number Theory in Science and Communication
Book Subtitle: With Applications in Cryptography, Physics, Digital Information, Computing, and Self-Similarity
Authors: Manfred R. Schroeder
Series Title: Springer Series in Information Sciences
DOI: https://doi.org/10.1007/978-3-662-03430-9
Publisher: Springer Berlin, Heidelberg
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eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag Berlin Heidelberg 1997
eBook ISBN: 978-3-662-03430-9Published: 29 June 2013
Series ISSN: 0720-678X
Edition Number: 3
Number of Pages: XXII, 364
Number of Illustrations: 94 b/w illustrations, 4 illustrations in colour
Topics: Number Theory, Mathematical Methods in Physics, Numerical and Computational Physics, Simulation, Coding and Information Theory, Probability Theory and Stochastic Processes