An Introduction to Symbolic Dynamics and Coding
An Introduction to Symbolic Dynamics and Coding
On the Entropy of a Hidden Markov Process
DCC '04 Proceedings of the Conference on Data Compression
An upper bound for the largest Lyapunov exponent of a Markovian product of nonnegative matrices
Theoretical Computer Science
On the optimality of symbol-by-symbol filtering and denoising
IEEE Transactions on Information Theory
Simulation-Based Computation of Information Rates for Channels With Memory
IEEE Transactions on Information Theory
Capacity of Finite State Channels Based on Lyapunov Exponents of Random Matrices
IEEE Transactions on Information Theory
Analyticity of Entropy Rate of Hidden Markov Chains
IEEE Transactions on Information Theory
Derivatives of Entropy Rate in Special Families of Hidden Markov Chains
IEEE Transactions on Information Theory
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 3
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We derive an asymptotic formula for entropy rate of a hidden Markov chain under certain parameterizations. We also discuss applications of the asymptotic formula to the asymptotic behaviors of entropy rate of hidden Markov chains as outputs of certain channels, such as binary symmetric channel, binary erasure channel, and some special Gilbert-Elliot channel.