limit entropy
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Entropy (information theory) — In information theory, entropy is a measure of the uncertainty associated with a random variable. The term by itself in this context usually refers to the Shannon entropy, which quantifies, in the sense of an expected value, the information… … Wikipedia
Entropy — This article is about entropy in thermodynamics. For entropy in information theory, see Entropy (information theory). For a comparison of entropy in information theory with entropy in thermodynamics, see Entropy in thermodynamics and information… … Wikipedia
Entropy (statistical thermodynamics) — In thermodynamics, statistical entropy is the modeling of the energetic function entropy using probability theory. The statistical entropy perspective was introduced in 1870 with the work of the Austrian physicist Ludwig Boltzmann. Mathematical… … Wikipedia
Entropy rate — The entropy rate of a stochastic process is, informally, the time density of the average information in a stochastic process. For stochastic processes with a countable index, the entropy rate H(X) is the limit of the joint entropy of n members of … Wikipedia
Entropy in thermodynamics and information theory — There are close parallels between the mathematical expressions for the thermodynamic entropy, usually denoted by S , of a physical system in the statistical thermodynamics established by Ludwig Boltzmann and J. Willard Gibbs in the 1870s; and the … Wikipedia
Principle of maximum entropy — This article is about the probability theoretic principle. For the classifier in machine learning, see maximum entropy classifier. For other uses, see maximum entropy (disambiguation). Bayesian statistics Theory Bayesian probability Probability… … Wikipedia
Topological entropy — In mathematics, the topological entropy of a topological dynamical system is a nonnegative real number that measures the complexity of the system. Topological entropy was first introduced in 1965 by Adler, Konheim and McAndrew. Their definition… … Wikipedia
Central limit theorem — This figure demonstrates the central limit theorem. The sample means are generated using a random number generator, which draws numbers between 1 and 100 from a uniform probability distribution. It illustrates that increasing sample sizes result… … Wikipedia
Rényi entropy — In information theory, the Rényi entropy, a generalisation of Shannon entropy, is one of a family of functionals for quantifying the diversity, uncertainty or randomness of a system. It is named after Alfréd Rényi. The Rényi entropy of order α,… … Wikipedia
Configuration entropy — In statistical mechanics, configuration entropy is the portion of a system s entropy that is related to the position of its constituent particles rather than to their velocity or momentum. It is physically related to the number of ways of… … Wikipedia
Differential entropy — (also referred to as continuous entropy) is a concept in information theory that extends the idea of (Shannon) entropy, a measure of average surprisal of a random variable, to continuous probability distributions. Contents 1 Definition 2… … Wikipedia
