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

discusses how information theory (a branch of mathematics studying the transmission, processing and storage of information) is related to measure theory (a branch...

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

Integrated information theory (IIT) proposes a mathematical model for the consciousness of a system. It comprises a framework ultimately intended to explain...

information theory (AIT) is a branch of theoretical computer science that concerns itself with the relationship between computation and information of...

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

until the late 19th and early 20th centuries that measure theory became a branch of mathematics. The foundations of modern measure theory were laid in the...

central concept of fuzzy measure theory is the fuzzy measure (also capacity, see ), which was introduced by Choquet in 1953 and independently defined by...

mathematics, computable measure theory is the part of computable analysis that deals with effective versions of measure theory. Jeremy Avigad (2012), "Inverting...

properties of the dynamics. Ergodic theory, like probability theory, is based on general notions of measure theory. Its initial development was motivated...