Markov Process

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.