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A random process whose future probabilities are determined by its most recent values. A stochastic process is called Markov if for every and , we have
This is equivalent to
(Papoulis 1984, p. 535).
REFERENCES:
Bharucha-Reid, A. T. Elements of the Theory of Markov Processes and Their Applications. New York: McGraw-Hill, 1960.
Papoulis, A. "Brownian Movement and Markoff Processes." Ch. 15 in Probability, Random Variables, and Stochastic Processes, 2nd ed. New York: McGraw-Hill, pp. 515-553, 1984.
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