2006•2006 IEEE International Conference on CommunicationsOpen access

Taylor series expansions for the entropy rate of Hidden Markov Processes

Or Zuk, Eytan Domany, Ido Kanter, Michael Aizenman

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Abstract

Finding the entropy rate of Hidden Markov Processes is an active research topic, of both theoretical and practical importance. A recently used approach is studying the asymptotic behavior of the entropy rate in various regimes. In this paper we generalize and prove a previous conjecture relating the entropy rate to entropies of finite systems. We use the proof to establish series expansions for the entropy rate in two different regimes. We also study the radius of convergence of the two series expansions.

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What this paper is about

Finding the entropy rate of Hidden Markov Processes is an active research topic, of both theoretical and practical importance. A recently used approach is studying the asymptotic behavior of the entropy rate in various regimes. In this paper we generalize and prove a previous conjecture relating the entropy rate to entropies of finite systems. We use the proof to establish series expansions for the entropy rate in two different regimes. We also study the radius of convergence of the two series expansions.

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Available abstract

Finding the entropy rate of Hidden Markov Processes is an active research topic, of both theoretical and practical importance. A recently used approach is studying the asymptotic behavior of the entropy rate in various regimes. In this paper we generalize and prove a previous conjecture relating the entropy rate to entropies of finite systems. We use the proof to establish series expansions for the entropy rate in two different regimes. We also study the radius of convergence of the two series expansions.

Key concepts: Entropy rate, Maximum-entropy Markov model, Radius of convergence, Entropy (arrow of time), Mathematics, Conjecture, Rate of convergence, Statistical physics

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