Title :
Asymptotics of the entropy rate for a hidden Markov process
Author :
Zuk, Or ; Kanter, Ido ; Domany, Eytan
Author_Institution :
Dept. of Phys. of Complex Syst., Weizmann Inst. of Sci., Israel
Abstract :
We calculate the Shannon entropy rate of a binary hidden Markov process (HMP), of given transition rate and noise ε (emission), as a series expansion in ε. The first two orders are calculated exactly. We then evaluate, for finite histories, simple upper-bounds of Cover and Thomas. Surprisingly, we find that for a fixed order k and history of n steps, the bounds become independent of n for large enough n. This observation is the basis of a conjecture, that the upper-bound obtained for n≥(k+3)/2 gives the exact entropy rate for any desired order k of ε.
Keywords :
entropy codes; hidden Markov models; series (mathematics); Shannon entropy rate; binary HMP; hidden Markov process; series expansion; transition rate; Bioinformatics; Biomedical signal processing; Entropy; Hidden Markov models; History; Machine learning; Markov processes; Physics; Speech recognition; Symmetric matrices;
Conference_Titel :
Data Compression Conference, 2005. Proceedings. DCC 2005
Print_ISBN :
0-7695-2309-9
DOI :
10.1109/DCC.2005.18