"An alphabet of events in which the probability of occurence of a given number of the alphabet is a function of the m preceeding occurences" (K. SAYRE, 1976, p.29)
This is the generalized case of the first-order MARKOV source, "one in which the identity of each successive event (each output event) is a probabilistic function of the event immediately preceeding (a specific input-event)".
K. SAYRE adds: "The mutual convertibility of a single alphabet information channel (a cascade of channels) with its corresponding MARKOV source is guaranteed by the fact that both can be completely characterized by a conditional probability matrix of the same basic form" (p.29-30).
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Bertalanffy Center for the Study of Systems Science (2020). Title of the entry. In Charles François (Ed.), International Encyclopedia of Systems and Cybernetics (2). Retrieved from www.systemspedia.org/[full/url]
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