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Contents: Information and Information Stability of Random Quantities--Probability Spaces, Information, Conditional Information, Information Stability; Rate of Information Generation and Information Stability of Random Processes-Definition of the Rate of Generation of Information and Information Stability of Random Processes, Rate of Information Generation and Information Stability of Stationary Random Processes in a Discrete Argument with a Finite Number of States, Rate of Information Generation on Stationary Random Processes (General Case), Information Stability of Stationary Random Processes; Information, Rate of Information Generation, and Information Stability of Normally distributed Random Variables and Processes-Information and Information Stability of Gaussian Random Variables, Calculation of the Rate of Information Generation for Gaussian Random Processes, Information Stability of Gaussian Random Process.
Contents: Information and Information Stability of Random Quantities--Probability Spaces, Information, Conditional Information, Information Stability; Rate of Information Generation and Information Stability of Random Processes-Definition of the Rate of Generation of Information and Information Stability of Random Processes, Rate of Information Generation and Information Stability of Stationary Random Processes in a Discrete Argument with a Finite Number of States, Rate of Information Generation on Stationary Random Processes (General Case), Information Stability of Stationary Random Processes; Information, Rate of Information Generation, and Information Stability of Normally distributed Random Variables and Processes-Information and Information Stability of Gaussian Random Variables, Calculation of the Rate of Information Generation for Gaussian Random Processes, Information Stability of Gaussian Random Process.
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.