FR4.R5.1

Ziv–Merhav estimation for hidden-Markov processes

Nicholas Barnfield, Raphaël Grondin, McGill University, Canada; Gaia Pozzoli, CY Cergy Paris Université, France; Renaud Raquépas, New York University, United States

Session:
Estimation 2

Track:
11: Information Theory and Statistics

Location:
Omikron I

Presentation Time:
Fri, 12 Jul, 16:25 - 16:45

Session Chair:
Andrew Thangaraj,
Abstract
We present a proof of strong consistency of a Ziv–Merhav-type estimator of the cross entropy rate for pairs of hidden-Markov processes. Our proof strategy has two novel aspects: the focus on decoupling properties of the laws and the use of tools from the thermodynamic formalism.
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