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Large deviations for empirical entropies of Gibbsian sources

J. -R. Chazottes·D. Gabrielli
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Abstract

The entropy of an ergodic finite-alphabet process can be computed from a single typical sample path x_1^n using the entropy of the k-block empirical probability and letting k grow with $n$ roughly like log n. We further assume that the distribution of the process is a g-measure; g-measures form a large class of Gibbs measures. We prove large deviation principles for conditional, non-conditional and relative k(n)-block empirical entropies.

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J. -R. Chazottes, D. Gabrielli. 2005-06-17. Large deviations for empirical entropies of Gibbsian sources. https://doi.org/10.1088/0951-7715%2F18%2F6%2F007

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