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:
“Rules and particular inferences alike are justified by being brought into agreement with each other. A rule is amended if it yields an inference we are unwilling to accept; an inference is rejected if it violates a rule we are unwilling to amend. The process of justification is the delicate one of making mutual adjustments between rules and accepted inferences; and in the agreement achieved lies the only justification needed for either.”
—Nelson Goodman (b. 1906)
“If you have any information or evidence regarding the O.J. Simpson case, press 2 now. If you are an expert in fields relating to the O.J. Simpson case and would like to offer your services, press 3 now. If you would like the address where you can send a letter of support to O.J. Simpson, press 1 now. If you are seeking legal representation from the law offices of Robert L. Shapiro, press 4 now.”
—Advertisement. Aired August 8, 1994 by Tom Snyder on TV station CNBC. Chicago Sun Times, p. 11 (July 24, 1994)