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Epsilon Entropy of Stochastic Processes With Continuous Paths
Edward C. Posner and Eugene R. Rodemich
The Annals of Probability
Vol. 1, No. 4 (Aug., 1973), pp. 674-689
Published by: Institute of Mathematical Statistics
Stable URL: http://www.jstor.org/stable/2959437
Page Count: 16
You can always find the topics here!Topics: Entropy, Stochastic processes, Covariance, Mathematical moments, Integers, Vertices, Continuous functions, Mathematical functions, Mathematics, Jet propulsion
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This paper shows that the epsilon entropy in the sup norm of a wide variety of processes with continuous paths on the unit interval is finite. In fact, the class coincides with the class of processes for which proofs of continuity have been given from a covariance condition. This suggests the conjecture that the epsilon entropy of any process continuous on the unit interval is finite in the sup norm of continuous functions. The epsilon entropy considered in this paper is defined as the minimum Shannon entropy of any partition by sets of diameter at most epsilon of the space of continuous functions on the unit interval, where the probability is the one inherited from the given process. The proof proceeds by constructing partitions and estimating their entropy using probability bounds.
The Annals of Probability © 1973 Institute of Mathematical Statistics