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W2022843495 abstract "Let {X t } be a stationary finite-alphabet Markov chain and {Z t } denote its noisy version when corrupted by a discrete memoryless channel. We present an approach to bounding the entropy rate of {Z t } by the construction and study of a related measure-valued Markov process. To illustrate its efficacy, we specialize it to the case of a BSC-corrupted binary Markov chain. The bounds obtained are sufficiently tight to characterize the behavior of the entropy rate in asymptotic regimes that exhibit a concentration of the support. Examples include the 'high SNR', 'low SNR', 'rare spikes', and 'weak dependence' regimes. Our analysis also gives rise to a deterministic algorithm for approximating the entropy rate, achieving the best known precision-complexity tradeoff, for a significant subset of the process parameter space" @default.
W2022843495 created "2016-06-24" @default.
W2022843495 creator A5006239162 @default.
W2022843495 creator A5043344688 @default.
W2022843495 date "2005-01-01" @default.
W2022843495 modified "2023-09-26" @default.
W2022843495 title "Approximations for the entropy rate of a hidden Markov process" @default.
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W2022843495 doi "https://doi.org/10.1109/isit.2005.1523737" @default.
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