You are not currently logged in.
Access your personal account or get JSTOR access through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
On the Entropy for Semi-Markov Processes
Valerie Girardin and Nikolaos Limnios
Journal of Applied Probability
Vol. 40, No. 4 (Dec., 2003), pp. 1060-1068
Published by: Applied Probability Trust
Stable URL: http://www.jstor.org/stable/3216060
Page Count: 9
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
The aim of this paper is to define the entropy of a finite semi-Markov process. We define the entropy of the finite distributions of the process, and obtain explicitly its entropy rate by extending the Shannon-McMillan-Breiman theorem to this class of nonstationary continuous-time processes. The particular cases of pure jump Markov processes and renewal processes are considered. The relative entropy rate between two semi-Markov processes is also defined.
Journal of Applied Probability © 2003 Applied Probability Trust