In probability theory and information theory, the mutual information (sometimes known by the archaic term transinformation) of two random variables is a quantity that measures the mutual dependence of the two random variables. The most common unit of measurement of mutual information is the bit, when logarithms to the base 2 are used.
Read more about Mutual Information: Definition of Mutual Information, Relation To Other Quantities, Variations of Mutual Information, Applications of Mutual Information
Famous quotes containing the words mutual and/or information:
“Every nation ... have their refinements and grossiertes.... There is a balance ... of good and bad every where; and nothing but the knowing it is so can emancipate one half of the world from the prepossessions which it holds against the other—that [was] the advantage of travel ... it taught us mutual toleration; and mutual toleration ... taught us mutual love.”
—Laurence Sterne (1713–1768)
“Computers are good at swift, accurate computation and at storing great masses of information. The brain, on the other hand, is not as efficient a number cruncher and its memory is often highly fallible; a basic inexactness is built into its design. The brain’s strong point is its flexibility. It is unsurpassed at making shrewd guesses and at grasping the total meaning of information presented to it.”
—Jeremy Campbell (b. 1931)