Entropy Rate and Maximum Entropy Methods for Countable Semi-Markov Chains

Abstract We are concerned with introducing entropy in the field of countable discrete-time semi-Markov process theory. We define the entropy of the finite distributions of the semi-Markov chain and obtain explicitly its entropy rate by extending the Shannon–McMillan–Breiman theorem to this class of non-stationary discrete-time processes. We also define the relative entropy rate between two semi-Markov chains. We then develop some maximum entropy methods for these processes.

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