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This book is devoted to the theory of probabilistic information measures and their application to coding theorems for information sources and noisy chan- nels. The eventual goal is a general development of Shannon's mathematical theory of communication, but much of the space is devoted to the tools and methods required to prove the Shannon coding theorems. These tools form an area common to ergodic theory and information theory and comprise several quantitative notions of the information in random variables, random processes, and dynamical systems | Entropy and Information Theory ii Entropy and Information Theory Robert M. Gray Information Systems Laboratory Electrical Engineering Department Stanford University Springer-Verlag New .