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

Abstract

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.