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130626 ||| eng |
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|a 9780387792347
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| 100 |
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|a Yeung, Raymond W.
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| 245 |
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|a Information Theory and Network Coding
|h Elektronische Ressource
|c by Raymond W. Yeung
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| 250 |
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|a 1st ed. 2008
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| 260 |
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|a New York, NY
|b Springer US
|c 2008, 2008
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| 300 |
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|a XX, 580 p
|b online resource
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| 505 |
0 |
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|a The Science of Information -- The Science of Information -- Fundamentals of Network Coding -- Information Measures -- Information Measures -- 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 -- Fundamentals of Network Coding -- 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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| 653 |
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|a Computer Communication Networks
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| 653 |
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|a Computer science
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| 653 |
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|a Data Structures and Information Theory
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| 653 |
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|a Probability Theory
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| 653 |
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|a Computer networks
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| 653 |
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|a Information theory
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| 653 |
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|a Telecommunication
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| 653 |
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|a Data structures (Computer science)
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| 653 |
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|a Communications Engineering, Networks
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| 653 |
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|a Theory of Computation
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| 653 |
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|a Probabilities
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Information Technology: Transmission, Processing and Storage
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| 028 |
5 |
0 |
|a 10.1007/978-0-387-79234-7
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| 856 |
4 |
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|u https://doi.org/10.1007/978-0-387-79234-7?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 004.0151
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| 520 |
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|a 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
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