Email this article Entropy of a stationary process and entropy of a shift transformation in its sample space
- Authors: Gurevich B.M.1,2
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Affiliations:
- Kharkevich Institute for Information Transmission Problems
- Lomonosov Moscow State University
- Issue: Vol 53, No 2 (2017)
- Pages: 103-113
- Section: Information Theory
- URL: https://journals.rcsi.science/0032-9460/article/view/166371
- DOI: https://doi.org/10.1134/S0032946017020016
- ID: 166371
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Abstract
We construct a class of non-Markov discrete-time stationary random processes with countably many states for which the entropy of the one-dimensional distribution is infinite, while the conditional entropy of the “present” given the “past” is finite and coincides with the metric entropy of a shift transformation in the sample space. Previously, such situation was observed in the case of Markov processes only.
About the authors
B. M. Gurevich
Kharkevich Institute for Information Transmission Problems; Lomonosov Moscow State University
Author for correspondence.
Email: bmgbmg2@gmail.com
Russian Federation, Moscow; Moscow
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