Information Theory and Coding Theory: 2nd Edition

Author: Michael Irwin
Publisher:
Publish Date: 2004-02-01
Features: This book is suitable as a textbook or reference for graduate or undergraduate students in information and communication engineering at universities. The dozens of examples and hundreds of exercises provided in the book also help those with some knowledge of probability theory and linear algebra to self-study. The book comprehensively and systematically introduces the main contents of information theory and coding theory proposed by Shannon in 1948, as well as some important research achievements in this field in recent decades. The author first introduces the basic ideas of information theory and coding theory to readers in the introduction. The first part explains the main contents of Shannon's information theory and coding theory, such as the basic concepts and properties of entropy and information quantity, as well as the channel coding theorem and source coding theorem. The second part introduces some channel and source coding methods based on Shannon's coding theory, including linear codes, cyclic codes, BCH and RS codes, convolutional codes, and variable-length source coding, among others. The book is rich in content and detailed, with clear and concise explanations of basic concepts and fundamental theories, while also fully reflecting the research progress in related fields.