The Measure-Theoretical Entropy of a Linear Cellular Automata with respect to a Markov Measure

Abstract

In this paper we study the measure-theoretical entropy of the one-dimensional linear cellular automata (CA hereafter) $T_{f[-l,r]}$, generated by local rule $f(x_{-l},...,x_{r})= \sum\limits_{i=-l}^{r}λ_{i}x_{i}(\text{mod}\ m)$, where $l$ and $r$ are positive integers, acting on the space of all doubly infinite sequences with values in a finite ring $\mathbb{Z}_{m}$, $m \geq 2$, with respect to a Markov measure. We prove that if the local rule $f$ is bipermutative, then the measure-theoretical entropy of linear CA $T_{f[-l,r]}$ with respect to a Markov measure $μ_{πP}$ is $ h_{μ_{πP}}(T_{f[-l,r]})=-(l+r)\sum\limits_{i,j=0}^{m-1}p_ip_{ij}\text{log} p_{ij}.$