Applications of communications theory
Description
The field of information theory and coding has developed into a vibrant and dynamic discipline that has revolutionized all aspects of information handling, storage, and communication. It has transformed our understanding of information in areas as diverse as biology, linguistics, and philosophy. This highly readable text provides a clear exposition of the fundamentals of discrete information theory and coding. The authors present in-depth discussions of the implications, interpretations, and examples of these basic principles, covering subjects that include information measures, Shannon's channel capacity/coding theorems, and source and channel coding concepts. Focusing on the results of practical applications of the material, the book features the use of Secret Agent 00111, a recurring character who solves information problems for a living and provides a concrete context for abstract theories; thorough treatment of noiseless self-synchronizing codes not found in any other book; a clear explanation of the Lempel-Ziv algorithm; problem sets used successfully with students at the University of Southern California. This instructive resource is written for readers with a knowledge of basic calculus and the elementary concepts of discrete probability theory. Basic Concepts in Information Theory and Coding makes an excellent and accessible introduction to the field for researchers, professionals, and graduate-level students in communication systems, computer science, and electrical systems science.
How the series evolves
Books in this Series
Basic concepts in information theory and coding
The field of information theory and coding has developed into a vibrant and dynamic discipline that has revolutionized all aspects of information handling, storage, and communication. It has transformed our understanding of information in areas as diverse as biology, linguistics, and philosophy. This highly readable text provides a clear exposition of the fundamentals of discrete information theory and coding. The authors present in-depth discussions of the implications, interpretations, and examples of these basic principles, covering subjects that include information measures, Shannon's channel capacity/coding theorems, and source and channel coding concepts. Focusing on the results of practical applications of the material, the book features the use of Secret Agent 00111, a recurring character who solves information problems for a living and provides a concrete context for abstract theories; thorough treatment of noiseless self-synchronizing codes not found in any other book; a clear explanation of the Lempel-Ziv algorithm; problem sets used successfully with students at the University of Southern California. This instructive resource is written for readers with a knowledge of basic calculus and the elementary concepts of discrete probability theory. Basic Concepts in Information Theory and Coding makes an excellent and accessible introduction to the field for researchers, professionals, and graduate-level students in communication systems, computer science, and electrical systems science.