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INFORMATION THEORY AND NETWORK CODING 2008 (H)
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ISBN: 9780387792330
類別: 電腦Computer Science & Engineering
出版社: SPRINGER
作者: YEUNG
年份: 2008
裝訂別: 精裝
頁數: 605
定價: 1,430
售價: 1,287
原幣價: EUR 44.95
狀態: 正常
About this textbook

。Features a modern treatment of information theory that combines with a new topic of network coding
。Includes numerous examples, illustrations, and original problems
。Structured systematically as a textbook and includes problems with solutions

Information Theory and Network Coding consists of two parts: Components of Information Theory, and Fundamentals of Network Coding Theory. Part I is a rigorous treatment of information theory for discrete and continuous systems. In addition to the classical topics, there are such modern topics as the I-Measure, Shannon-type and non-Shannon-type information inequalities, and a fundamental relation between entropy and group theory. With information theory as the foundation, Part II is a comprehensive treatment of network coding theory with detailed discussions on linear network codes, convolutional network codes, and multi-source network coding.

Other important features include:

.Derivations that are from the first principle

.A large number of examples throughout the book

.Many original exercise problems

.Easy-to-use chapter summaries

.Two parts that can be used separately or together for a comprehensive course

Information Theory and Network Coding is for senior undergraduate and graduate students in electrical engineering, computer science, and applied mathematics. This work can also be used as a reference for professional engineers in the area of communications.

Table of contents

The Science of Information.- Part I: Components of Information Theory. Information Measures. The I-Measure. Zero-Error Data Compression. Weak Typicality. Strong Typicality. Discrete Memoryless Channels. Rate Distortion Theory. The Blahut-Arimoto Algorithms. Differential Entropy. Continuous-Valued Channels. Markov Structures. Information Inequalities. Shannon-Type Inequalities. Beyond Shannon-Type Inequalities. Entropy and Groups.- Part II: Fundamentals of Network Coding. Introduction. The Max-Flow Bound. Single-Source Linear Network Coding: Acyclic Networks. Single-Source Linear Network Coding: Cyclic Networks.- Multi-Source Network Coding.

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