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Information Theory addresses the following questions: There are two fundamental theorems by Shannon that address these questions. First we deﬁne a few quantities. Typically, the source data is unknown, and we can treat the input data as a random variable, for instance, ﬂipping coins and sending that as input across the channel to test the communication scheme. We deﬁne the entropy of
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a) For a valid and correctly received code word, When C is the code word and His the parity-check paatrix. b) RSAalgo ’ c) Shannon’s theorems (three) in communication.
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– Information Theory is about quantification of information. – It is used in compressing data. – Entropy is a key measure of information. – It is expressed in terms of average number of bits that are required to store a message.
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“Information Theory” answers two fundamental questions in communication theory： • What is the ultimate data compression? (answer: the entropy of the data, H, is its compression limit.) •What is the ultimate transmission rate of communication? (answer: the channel capacity, C, is its rate limit.) It founds the most basic theoretical foundations of communication theory. Information
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