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Paper IDS.11.1
Paper Title Rényi Divergence rates of Ergodic Markov Chains: existence, explicit expressions and properties
Authors Valérie Girardin, Laboratoire de Mathématiques Nicolas Oresme, France; Philippe Regnault, Laboratoire de Mathématiques de Reims, France
Session S.11: Renyi Entropy
Presentation Lecture
Track Shannon Theory
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Abstract The Kullback-Leibler divergence rate of two finite or denumerable ergodic Markov chains is well-known to exist and have an explicit expression as a function of the transition matrices of the chains, allowing access to classical tools for applications, such as minimization under constraints or projections on convex sets. The existence of Rényi divergence rates of ergodic Markov chains has been established in Rached et al. (2001), Girardin and Lhote (2015); here we establish explicit expressions for them and prove some properties of the resulting measures of discrepancy between stochastic matrices, opening the way to applications.

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2021 IEEE International Symposium on Information Theory

11-16 July 2021 | Melbourne, Victoria, Australia

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