Small deviation properties concerning arrays of non-homogeneous Markov information sources

Ximei Qin; Zhaobiao Rui; Shu Chen; Shu Chen; Weicai Peng

doi:10.3389/fphy.2023.1156610

Frontiers in Physics (Mar 2023)

Small deviation properties concerning arrays of non-homogeneous Markov information sources

Ximei Qin,
Zhaobiao Rui,
Shu Chen,
Shu Chen,
Weicai Peng

Affiliations

Ximei Qin: School of Mathematics and Big Data, Chaohu University, Hefei, China
Zhaobiao Rui: School of Mathematics and Big Data, Chaohu University, Hefei, China
Shu Chen: School of Mathematics and Big Data, Chaohu University, Hefei, China
Shu Chen: School of Microelectronics and Data Science, Anhui University of Technology, Ma’anshan, China
Weicai Peng: School of Mathematics and Big Data, Chaohu University, Hefei, China

DOI: https://doi.org/10.3389/fphy.2023.1156610
Journal volume & issue: Vol. 11

Abstract

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In this study, we first define the logarithmic likelihood ratio as a measure between arbitrary generalized information sources and non-homogeneous Markov sources and then establish a class of generalized information sources for small deviation theorems, strong limit theorems, and the asymptotic equipartition property. The present outcomes generalize some existing results.

Published in Frontiers in Physics

ISSN: 2296-424X (Online)
Publisher: Frontiers Media S.A.
Country of publisher: Switzerland
LCC subjects: Science: Physics
Website: https://www.frontiersin.org/journals/physics

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