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Théorie de l'information : trois théorèmes de Claude Shannon par Antoine Chambert-Loir

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Caractéristiques de l'objet

État
Entièrement neuf: Un livre neuf, non lu, non utilisé et en parfait état, sans aucune page manquante ...
Book Title
Information Theory: Three Theorems by Claude Shannon
Publication Date
2023-03-16
ISBN
9783031215605

À propos de ce produit

Product Identifiers

Publisher
Springer International Publishing A&G
ISBN-10
3031215605
ISBN-13
9783031215605
eBay Product ID (ePID)
26058385943

Product Key Features

Number of Pages
Xii, 209 Pages
Publication Name
Information Theory : Three Theorems of Claude Shannon
Language
English
Publication Year
2023
Subject
Information Theory, Computer Science, General, Applied
Type
Textbook
Author
Antoine Chambert-Loir
Subject Area
Mathematics, Computers, Science
Series
Unitext Ser.
Format
Trade Paperback

Dimensions

Item Weight
15.1 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Reviews
"This book can be especially useful for those who are just getting to know the basics of information theory." (Eszter Gselmann, zbMATH 1526.94001, 2024)
Dewey Edition
23
Series Volume Number
144
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
003.54
Original Language
French
Table Of Content
Elements of Theory of Probability.- Entropy and Mutual Information.- Coding.- Sampling.- Solutions to Exercises.- Bibliography.- Notation.- Index.
Synopsis
This book provides an introduction to information theory, focussing on Shannon's three foundational theorems of 1948-1949. Shannon's first two theorems, based on the notion of entropy in probability theory, specify the extent to which a message can be compressed for fast transmission and how to erase errors associated with poor transmission. The third theorem, using Fourier theory, ensures that a signal can be reconstructed from a sufficiently fine sampling of it. These three theorems constitute the roadmap of the book. The first chapter studies the entropy of a discrete random variable and related notions. The second chapter, on compression and error correcting, introduces the concept of coding, proves the existence of optimal codes and good codes (Shannon's first theorem), and shows how information can be transmitted in the presence of noise (Shannon's second theorem). The third chapter proves the sampling theorem (Shannon's third theorem) and looks at its connections with other results, such as the Poisson summation formula. Finally, there is a discussion of the uncertainty principle in information theory. Featuring a good supply of exercises (with solutions), and an introductory chapter covering the prerequisites, this text stems out lectures given to mathematics/computer science students at the beginning graduate level.
LC Classification Number
QA76.9.M35

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