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7. Aug. 2020 · Entropy as best achievable rate of compression: The second angle views entropy as a limit to how efficiently we can communicate the outcome of this random variable – that is, how much we can “compress” it. This latter angle will provide some insight into how to understand the logarithm in the self-information function.
6. Juni 2020 · In this section, we briefly review some key applications connecting information theory with optimization, notably through Maximum Entropy Production (MEP) and then discuss information theory in the context of dimensionality reduction for omics analysis. 3.7.1. Optimization in Biology.
11.3 Basics of Large deviation theory. Chapter 12: Information projection and Large deviation (PDF) 12.1 Large-deviation exponents. 12.2 Information Projection. 12.3 Interpretation of Information Projection. 12.4 Generalization: Sanov’s theorem. Chapter 13: Hypothesis testing asymptotics II (PDF - 2.0MB) 13.1 (E0,E1)-Tradeoff
In information theory, the conditional entropy quantifies the amount of information needed to describe the outcome of a random variable given that the value of another random variable is known. Here, information is measured in shannons, nats, or hartleys. The entropy of conditioned on is written as .
Elements of Information Theory, by Thomas M. Cover and Joy A Thomas, Wiley, 1991. A readable and very enjoyable survey at the undergraduate level. Covers the equipartition theorem, Shannon's coding theorems, maximal entropy, discrimination and the theory of types (see Entropy in Statistical Inference and Prediction), and much more.
29. Nov. 2019 · This article is about the profound misuses, misunderstanding, misinterpretations and misapplications of entropy, the Second Law of Thermodynamics and Information Theory. It is the story of the “Greatest Blunder Ever in the History of Science”. It is not about a single blunder admitted by a single person (e.g., Albert Einstein allegedly said in connection with the cosmological constant ...
28. Apr. 2014 · Finally we arrive at our quantitative measure of entropyWatch the next lesson: https://www.khanacademy.org/computing/computer-science/informationtheory/moder...
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