Relative entropy between Markov transition rate matrices

G. Kesidis; J. Walrand

doi:10.1109/18.256516

Relative entropy between Markov transition rate matrices

G. Kesidis, J. Walrand

Research output: Contribution to journal › Article › peer-review

28 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 language	English (US)
Pages (from-to)	1056-1057
Number of pages	2
Journal	IEEE Transactions on Information Theory
Volume	39
Issue number	3
DOIs	https://doi.org/10.1109/18.256516
State	Published - 1993

All Science Journal Classification (ASJC) codes

Information Systems
Computer Science Applications
Library and Information Sciences

Access to Document

10.1109/18.256516

Cite this

@article{0634bce65fdf490694e1a3dd81fb3701,

title = "Relative entropy between Markov transition rate matrices",

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.",

author = "G. Kesidis and J. Walrand",

year = "1993",

doi = "10.1109/18.256516",

language = "English (US)",

volume = "39",

pages = "1056--1057",

journal = "IEEE Transactions on Information Theory",

issn = "0018-9448",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "3",

}

TY - JOUR

T1 - Relative entropy between Markov transition rate matrices

AU - Kesidis, G.

AU - Walrand, J.

PY - 1993

Y1 - 1993

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0027599156&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0027599156&partnerID=8YFLogxK

U2 - 10.1109/18.256516

DO - 10.1109/18.256516

M3 - Article

AN - SCOPUS:0027599156

SN - 0018-9448

VL - 39

SP - 1056

EP - 1057

JO - IEEE Transactions on Information Theory

JF - IEEE Transactions on Information Theory

IS - 3

ER -

Relative entropy between Markov transition rate matrices

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this