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In this context, either an information-theoretical measure, such as functional clusters (Gerald Edelman and Giulio Tononi's functional clustering model and dynamic core hypothesis (DCH) [47]) or effective information (Tononi's integrated information theory (IIT) of consciousness [48] [49] [50]), is defined (on the basis of a reentrant process ...
There is an analogy between Shannon's basic "measures" of the information content of random variables and a measure over sets. Namely the joint entropy , conditional entropy , and mutual information can be considered as the measure of a set union , set difference , and set intersection , respectively (Reza pp. 106–108).
The on-line textbook: Information Theory, Inference, and Learning Algorithms, by David J.C. MacKay, contains chapters on elementary error-correcting codes; on the theoretical limits of error-correction; and on the latest state-of-the-art error-correcting codes, including low-density parity-check codes, turbo codes, and fountain codes.
Donald M. MacKay says that information is a distinction that makes a difference. [4] According to Luciano Floridi [citation needed], four kinds of mutually compatible phenomena are commonly referred to as "information": Information about something (e.g. a train timetable) Information as something (e.g. DNA, or fingerprints)
Landauer's principle is a physical principle pertaining to a lower theoretical limit of energy consumption of computation.It holds that an irreversible change in information stored in a computer, such as merging two computational paths, dissipates a minimum amount of heat to its surroundings. [1]
Phi; the symbol used for integrated information. Integrated information theory (IIT) proposes a mathematical model for the consciousness of a system. It comprises a framework ultimately intended to explain why some physical systems (such as human brains) are conscious, [1] and to be capable of providing a concrete inference about whether any physical system is conscious, to what degree, and ...
In information theory, the entropy of a random variable quantifies the average level of uncertainty or information associated with the variable's potential states or possible outcomes. This measures the expected amount of information needed to describe the state of the variable, considering the distribution of probabilities across all potential ...
Information theory is the scientific study of the quantification, storage, and communication of information. The field itself was fundamentally established by the work of Claude Shannon in the 1940s, with earlier contributions by Harry Nyquist and Ralph Hartley in the 1920s.