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An introduction to information Theory and Entropy

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An introduction to information Theory and Entropy

An introduction to information Theory and Entropy

This note covers Measuring complexity, Some probability ideas, Basics of information theory, Some entropy theory, The Gibbs inequality, A simple physical example Shannon’s communication theory, Application to Biology, Examples using Bayes Theorem, Analog channels, A Maximum Entropy Principle, Application to Physics(lasers), Kullback-Leibler information measure.

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s139 Pages
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