THE ASYMPTOTIC EQUIPARTITION PROPERTY FOR ASYMPTOTIC CIRCULAR MARKOV CHAINS
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Publication:3564640
DOI10.1017/S0269964809990271zbMath1195.60102MaRDI QIDQ3564640
Peipei Liang, Pingping Zhong, Wei-guo Yang
Publication date: 26 May 2010
Published in: Probability in the Engineering and Informational Sciences (Search for Journal in Brave)
Related Items (11)
SOME LIMIT THEOREMS OF DELAYED AVERAGES FOR COUNTABLE NONHOMOGENEOUS MARKOV CHAINS ⋮ THE STRONG LIMIT THEOREM FOR RELATIVE ENTROPY DENSITY RATES BETWEEN TWO ASYMPTOTICALLY CIRCULAR MARKOV CHAINS ⋮ A NOTE ON RÉNYI'S ENTROPY RATE FOR TIME-INHOMOGENEOUS MARKOV CHAINS ⋮ The generalized entropy ergodic theorem for nonhomogeneous Markov chains ⋮ Strong law of large numbers for generalized sample relative entropy of non homogeneous Markov chains ⋮ Limit theorems for asymptotic circular mth-order Markov chains indexed by an m-rooted homogeneous tree ⋮ Strong Law of Large Numbers for Countable Asymptotic Circular Markov Chains ⋮ The strong law of large numbers for moving average of continuous state nonhomogeneous Markov chains ⋮ Markov approximation and the generalized entropy ergodic theorem for non-null stationary process ⋮ Asymptotic equipartition property for second-order circular Markov chains indexed by a two-rooted Cayley tree ⋮ Erratum to “THE ASYMPTOTIC EQUIPARTITION PROPERTY FOR ASYMPTOTIC CIRCULAR MARKOV CHAINS” [Probability in the Engineering and Informational Sciences, 24, 2010, 279–288]
Cites Work
- A Mathematical Theory of Communication
- Strong law of large numbers for countable nonhomogeneous Markov chains
- The strong ergodic theorem for densities: Generalized Shannon-McMillan- Breiman theorem
- The convergence of Cesaro averages for certain nonstationary Markov chains
- Large deviations for a class of nonhomogeneous Markov chains
- A simple proof of the Moy-Perez generalization of the Shannon-McMillan theorem
- Convergence in the Cesàro sense and strong law of large numbers for nonhomogeneous Markov chains
- A Note on the Ergodic Theorem of Information Theory
- The Basic Theorems of Information Theory
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