Suppose that ${X_n; Y_n}$ is a random process with a discrete alphabet, that is, taking on values in a discrete set for $n$ data length. They correspond to the input and output of a communication process. Assuming Y to be the discretized output, what is meant by Shannon's source entropy for a given discretization bin $k$ : $H_{source} = lim_{k \rightarrow \infty} \frac{1}{k} H_k$ where $H_k$ stands for Shannons entropy.
I found this in Stojanovski et al's paper: Applications of Symbolic Dynamics in Chaos Synchronization. Now, Jun Chen also mentions about source entropy but the formula is very different! Its the same as Shannon's entropy.
So, what exactly is source entropy? Is it the entropy of $X$ or $Y$ or is it the same as Shannon's entropy?