Non-asymptotic and asymptotic analyses on Markov chains in several problems

Abstract

In this paper, we derive non-asymptotic achievability and converse bounds on the source coding with side-information and the random number generation with side-information. Our bounds are efficiently computable in the sense that the computational complexity does not depend on the block length. We also characterize the asymptotic behaviors of the large deviation regime and the moderate deviation regime by using our bounds, which implies that our bounds are asymptotically tight in those regimes. We also show the second order rates of those problems, and derive single letter forms of the variances characterizing the second order rates.