This book contains a thorough discussion of the classical topics in information theory together with the first comprehensive treatment of network coding, asubject first emerged under information theory in the mid 1990's that has nowdiffused into coding theory, computer networks, wireless communications, complexity theory, cryptography, graph theory, etc. With a large number of examples, illustrations, and original problems, this book is excellent as a textbook or reference book for a senior or graduate level course on the subject, as well as a reference for researchers in related fields. Modern treatment of information theory that combines with new topic of network coding Includes numerous examples, illustrations, and original problems Structured systematically as a textbook and includes problems with solutions INDICE: 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: Fundamentalsof 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.
- ISBN: 978-0-387-79233-0
- Editorial: Springer
- Encuadernacion: Cartoné
- Páginas: 605
- Fecha Publicación: 01/08/2008
- Nº Volúmenes: 1
- Idioma: Inglés