This book is an updated version of the information theory classic, first published in 1990. About one-third of the book is devoted to Shannon source and channel coding theorems; the remainder addresses sources, channels, and codes and on information and distortion measures and their properties. New in this edition: • Expanded treatment of stationary or sliding-block codes and their relations to traditional block codes • Expanded discussion of results from ergodic theory relevant to information theory • Expanded treatment of B-processes processes formed by stationary coding memoryless sources • New material on trading off information and distortion, including the Marton inequality • New material on the properties of optimal and asymptotically optimal source codes • New material on the relationships of source coding and rate-constrained simulation or modeling of random processes Significant material not covered in other information theory texts includes stationary/sliding-block codes, a geometric view of information theory provided by process distance measures, and general Shannon coding theorems for asymptotic mean stationary sources, which may be neither ergodic nor stationary, and d-bar continuous channels.
This book is an updated version of the information theory classic, first published in 1990. About one-third of the book is devoted to Shannon source and channel coding theorems; the remainder addresses sources, channels, and codes and on information and distortion measures and their properties. New in this edition: • Expanded treatment of stationary or sliding-block codes and their relations to traditional block codes • Expanded discussion of results from ergodic theory relevant to information theory • Expanded treatment of B-processes processes formed by stationary coding memoryless sources • New material on trading off information and distortion, including the Marton inequality • New material on the properties of optimal and asymptotically optimal source codes • New material on the relationships of source coding and rate-constrained simulation or modeling of random processes Significant material not covered in other information theory texts includes stationary/sliding-block codes, a geometric view of information theory provided by process distance measures, and general Shannon coding theorems for asymptotic mean stationary sources, which may be neither ergodic nor stationary, and d-bar continuous channels.
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