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In information theory, ambiguity refers to the capacity of a communication channel to generate multiple interpretations of the same message. This ambiguity is defined by measuring the average entropy of the source, considered as a whole and applied to all transmitted symbols. To better understand this concept, Jean Hebenstreit explains that transinformation represents the actual amount of information transmitted through a channel affected by noise. When the ambiguity is zero, that is, in the absence of disturbances, transinformation reaches its maximum, equivalent to the entropy of the source (H(A)).

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