Positions have a finite number of possible states {information}. Positions can be static, as in memories or registers, or moving, as in information channels. Mathematical rules {information theory, data} describe storing, retrieving, and transmitting data.
information extraction from data
States differ from other states, so information extraction at locations notes differences, rather than measuring amounts. Information is any difference, change, or possible-set selection.
Sampling theorems, such as Logan's zero-crossing theorem, describe how to extract information from data.
probability
States have probabilities of being at locations. If location has states at random, there is no information, even if states have known transitions. Non-random conditional probability is information.
system
Finite systems have finite numbers of elements, which have finite numbers of states. Systems are information spaces, and distributions are information sets. Highest probability has the most possible states. Some outputs are typically more probable than others.
dependence
Difference between sum of independent entropies and actual system entropy measures dependence. System subsets can depend on whole system {mutual information}.
Mathematical Sciences>Information Theory>Information
3-Information Theory-Information
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Date Modified: 2022.0224