An efficient algorithm for the entropy rate of a hidden Markov model with unambiguous symbols
Jaideep Mulherkar
Abstract
Open-access reader
Jaideep Mulherkar
Abstract
Open-access reader
We demonstrate an efficient formula to compute the entropy rate $H(μ)$ of a hidden Markov process with $q$ output symbols where at least one symbol is unambiguously received. Using an approximation to $H(μ)$ to the first $N$ terms we give a $O(Nq^3$) algorithm to compute the entropy rate of the hidden Markov model. We use the algorithm to estimate the entropy rate when the parameters of the hidden Markov model are unknown.In the case of $q =2$ the process is the output of the Z-channel and we use this fact to give bounds on the capacity of the Gilbert channel.
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We demonstrate an efficient formula to compute the entropy rate $H(μ)$ of a hidden Markov process with $q$ output symbols where at least one symbol is unambiguously received. Using an approximation to $H(μ)$ to the first $N$ terms we give a $O(Nq^3$) algorithm to compute the entropy rate of the hidden Markov model. We use the algorithm to estimate the entropy rate when the parameters of the hidden Markov model are unknown.In the case of $q =2$ the process is the output of the Z-channel and we use this fact to give bounds on the capacity of the Gilbert channel.
Key concepts: Maximum-entropy Markov model, Hidden Markov model, Hidden semi-Markov model, Markov model, Entropy rate, Markov chain, Markov process, Entropy (arrow of time)