A class of small deviation theorems for the random variables associated withmth-order asymptotic circular Markov chains
DOI10.1080/03610926.2014.972746zbMath1352.60043OpenAlexW2513370128MaRDI QIDQ2834655
Bei Wang, Zhiyan Shi, Wei-guo Yang
Publication date: 23 November 2016
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2014.972746
strong law of large numbersasymptotic equipartition propertysmall deviation theoremasymptotic circular Markov chains
Strong limit theorems (60F15) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Large deviations (60F10)
Related Items (2)
Cites Work
- A Mathematical Theory of Communication
- Strong law of large numbers for Markov chains indexed by an infinite tree with uniformly bounded degree
- Some limit properties for the \(m\)th-order nonhomogeneous Markov chains indexed by an m rooted Cayley tree
- A class of random deviation theorems and the approach of Laplace transform
- The strong ergodic theorem for densities: Generalized Shannon-McMillan- Breiman theorem
- A sandwich proof of the Shannon-McMillan-Breiman theorem
- Some limit properties for Markov chains indexed by a homogeneous tree.
- Large deviations for a class of nonhomogeneous Markov chains
- Convergence in the Cesàro sense and strong law of large numbers for nonhomogeneous Markov chains
- The Markov approximation of the sequences of \(N\)-valued random variables and a class of small deviation theorems.
- An extension of Shannon-McMillan theorem and some limit properties for nonhomogeneous Markov chains
- The Asymptotic Equipartition Property for<tex>$M$</tex>th-Order Nonhomogeneous Markov Information Sources
- The Asymptotic Equipartition Property for Nonhomogeneous Markov Chains Indexed by a Homogeneous Tree
- A Note on the Ergodic Theorem of Information Theory
- The Basic Theorems of Information Theory
This page was built for publication: A class of small deviation theorems for the random variables associated withmth-order asymptotic circular Markov chains