Information Theory: Coding Theorems for Discrete Memoryless Systems presents mathematical models that involve independent random variables with finite range. This three-chapter text specifically describes the characteristic phenomena of information theory.
Chapter 1 deals with information measures in simple coding problems, with emphasis on some formal properties of Shannon's information and the non-block source coding. Chapter 2 describes the properties and practical aspects of the two-terminal systems. This chapter also examines the noisy channel coding problem, the computation of channel capacity, and the arbitrarily varying channels. Chapter 3 looks into the theory and practicality of multi-terminal systems.
This book is intended primarily for graduate students and research workers in mathematics, electrical engineering, and computer science.
Inhalt
Introduction
Basic Notations and Conventions
1. Information Measures in Simple Coding Problems
§ 1. Source Coding and Hypothesis Testing. Information Measures
§ 2. Types and Typical Sequences
§ 3. Some Formal Properties of Shannon's Information Measures
§ 4. Non-Block Source Coding
§ 5. Blowing Up Lemma: A Combinatorial Digression
2. Two-Terminal Systems
§ 1. The Noisy Channel Coding Problem
§ 2. Rate-Distortion Trade-Off in Source Coding and the Source-Channel Transmission Problem
§ 3. Computation of Channel Capacity and -Distortion Rates
§4. A Covering Lemma. Error Exponent in Source Coding
§5. A Packing Lemma. On the Error Exponent in Channel Coding
§ 6. Arbitrarily Varying Channels
3. Multi-Terminal Systems
§ 1. Separate Coding of Correlated Source
§ 2. Multiple-Access Channels
§ 3. Entropy and Image Size Characterization
§ 4. Source and Channel Networks
References
Name Index
Subject Index
Index of Symbols and Abbreviations