Relative entropy between Markov transition rate matrices

G. Kesidis, J. Walrand

Research output: Contribution to journalArticle

24 Scopus citations

Abstract

The relative entropy between two Markov transition rate matrices from sample path considerations is derived. This relative entropy is interpreted as a 'level 2.5' large deviations action functional. That is, the level two large deviations action functional for empirical distributions of continuous-time Markov chains can be derived from the relative entropy using the contraction mapping principle.

Original languageEnglish (US)
Pages (from-to)1056-1057
Number of pages2
JournalIEEE Transactions on Information Theory
Volume39
Issue number3
DOIs
StatePublished - May 1 1993

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

Fingerprint Dive into the research topics of 'Relative entropy between Markov transition rate matrices'. Together they form a unique fingerprint.

  • Cite this