In information theory, the entropy of a random variable quantifies the average level of uncertainty or information associated with the variable's potential...

similar to the information entropy by Claude Shannon and Ralph Hartley, developed in the 1940s. The defining expression for entropy in the theory of statistical...

in information theory are mutual information, channel capacity, error exponents, and relative entropy. Important sub-fields of information theory include...

In information theory, the Rényi entropy is a quantity that generalizes various notions of entropy, including Hartley entropy, Shannon entropy, collision...

Differential entropy (also referred to as continuous entropy) is a concept in information theory that began as an attempt by Claude Shannon to extend...

In information theory, the conditional entropy quantifies the amount of information needed to describe the outcome of a random variable Y {\displaystyle...

In statistics and information theory, a maximum entropy probability distribution has entropy that is at least as great as that of all other members of...

arguing that the entropy of statistical mechanics and the information entropy of information theory are the same concept. Consequently, statistical mechanics...

message source Differential entropy, a generalization of Entropy (information theory) to continuous random variables Entropy of entanglement, related to...

In information theory, an entropy coding (or entropy encoding) is any lossless data compression method that attempts to approach the lower bound declared...

In information theory, joint entropy is a measure of the uncertainty associated with a set of variables. The joint Shannon entropy (in bits) of two discrete...

uncertainty) entropy encoding entropy (information theory) Fisher information Hick's law Huffman coding information bottleneck method information theoretic...

In the mathematical theory of probability, the entropy rate or source information rate is a function assigning an entropy to a stochastic process. For...

The joint quantum entropy generalizes the classical joint entropy to the context of quantum information theory. Intuitively, given two quantum states ρ...

concept of mutual information is intimately linked to that of entropy of a random variable, a fundamental notion in information theory that quantifies the...

used measure of information content, now known as Shannon entropy. As an objective measure of the quantity of information, Shannon entropy has been enormously...

In information theory, redundancy measures the fractional difference between the entropy H(X) of an ensemble X, and its maximum possible value log ⁡ (...

relative entropies, etc.) in the framework of quantum information theory to characterize the entropy of entanglement. John von Neumann established a rigorous...

In information theory and statistics, negentropy is used as a measure of distance to normality. The concept and phrase "negative entropy" was introduced...

random variable. The Shannon information is closely related to entropy, which is the expected value of the self-information of a random variable, quantifying...

science, climate change, and information systems including the transmission of information in telecommunication. Entropy is central to the second law...

In information theory, the cross-entropy between two probability distributions p {\displaystyle p} and q {\displaystyle q} , over the same underlying...

distance Information gain in decision trees Information gain ratio Information theory and measure theory Jensen–Shannon divergence Quantum relative entropy Solomon...

entropy is an entropy measure used in quantum information theory. It is a generalization of the conditional entropy of classical information theory....

In information theory, the binary entropy function, denoted H ⁡ ( p ) {\displaystyle \operatorname {H} (p)} or H b ⁡ ( p ) {\displaystyle \operatorname...

In quantum information theory, quantum relative entropy is a measure of distinguishability between two quantum states. It is the quantum mechanical analog...

In statistical mechanics, entropy is formulated as a statistical property using probability theory. The statistical entropy perspective was introduced...

using quantum information processing techniques. Quantum information refers to both the technical definition in terms of Von Neumann entropy and the general...

Quantum Fisher information Other measures employed in information theory: Entropy (information theory) Kullback–Leibler divergence Self-information Robert, Christian...

Teachers of History proposing a theory of history based on the second law of thermodynamics and on the principle of entropy. The 1944 book What is Life?...