  In this paper we investigate a quantity called conditional entropy of ordinal
patterns, akin to the permutation entropy. The conditional entropy of ordinal
patterns describes the average diversity of the ordinal patterns succeeding a
given ordinal pattern. We observe that this quantity provides a good estimation
of the Kolmogorov-Sinai entropy in many cases. In particular, the conditional
entropy of ordinal patterns of a finite order coincides with the
Kolmogorov-Sinai entropy for periodic dynamics and for Markov shifts over a
binary alphabet. Finally, the conditional entropy of ordinal patterns is
computationally simple and thus can be well applied to real-world data.
