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===Source theory=== Any process that generates successive messages can be considered a {{em|[[Communication source|source]]}} of information. A memoryless source is one in which each message is an [[Independent identically distributed random variables|independent identically distributed random variable]], whereas the properties of [[ergodic theory|ergodicity]] and [[stationary process|stationarity]] impose less restrictive constraints. All such sources are [[stochastic process|stochastic]]. These terms are well studied in their own right outside information theory. ====Rate====<!-- This section is linked from [[Channel capacity]] --> Information ''[[Entropy rate|rate]]'' is the average entropy per symbol. For memoryless sources, this is merely the entropy of each symbol, while, in the case of a stationary stochastic process, it is: :<math>r = \lim_{n \to \infty} H(X_n|X_{n-1},X_{n-2},X_{n-3}, \ldots);</math> that is, the conditional entropy of a symbol given all the previous symbols generated. For the more general case of a process that is not necessarily stationary, the ''average rate'' is: :<math>r = \lim_{n \to \infty} \frac{1}{n} H(X_1, X_2, \dots X_n);</math> that is, the limit of the joint entropy per symbol. For stationary sources, these two expressions give the same result.<ref>{{cite book | title = Digital Compression for Multimedia: Principles and Standards | author = Jerry D. Gibson | publisher = Morgan Kaufmann | year = 1998 | url = https://books.google.com/books?id=aqQ2Ry6spu0C&q=entropy-rate+conditional&pg=PA56 | isbn = 1-55860-369-7 }}</ref> The [[information rate]] is defined as: :<math>r = \lim_{n \to \infty} \frac{1}{n} I(X_1, X_2, \dots X_n;Y_1,Y_2, \dots Y_n);</math> It is common in information theory to speak of the "rate" or "entropy" of a language. This is appropriate, for example, when the source of information is English prose. The rate of a source of information is related to its redundancy and how well it can be compressed, the subject of {{em|source coding}}.
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