TY - GEN
T1 - Modeling non stationary hidden semi-Markov chains with triplet Markov chains and theory of evidence
AU - Pieczynski, Wojciech
PY - 2005/1/1
Y1 - 2005/1/1
N2 - Hidden Markov chains, enabling one to recover the hidden process even for very large size, are widely used in various problems. On the one hand, it has been recently established that when the hidden chain is not stationary, the use of the theory of evidence is equivalent to consider a triplet Markov chain and can improve the efficiency of unsupervised segmentation. On the other hand, hidden semi-Markov chains can also be considered as particular triplet Markov chains. The aim of this paper is to use these two points simultaneously. Considering a non stationary hidden semi-Markov chain, we show that it is possible to consider two auxiliary random chains in such a way that unsupervised segmentation of non stationary hidden semi-Markov chains is workable.
AB - Hidden Markov chains, enabling one to recover the hidden process even for very large size, are widely used in various problems. On the one hand, it has been recently established that when the hidden chain is not stationary, the use of the theory of evidence is equivalent to consider a triplet Markov chain and can improve the efficiency of unsupervised segmentation. On the other hand, hidden semi-Markov chains can also be considered as particular triplet Markov chains. The aim of this paper is to use these two points simultaneously. Considering a non stationary hidden semi-Markov chain, we show that it is possible to consider two auxiliary random chains in such a way that unsupervised segmentation of non stationary hidden semi-Markov chains is workable.
UR - https://www.scopus.com/pages/publications/33947128657
U2 - 10.1109/ssp.2005.1628689
DO - 10.1109/ssp.2005.1628689
M3 - Conference contribution
AN - SCOPUS:33947128657
SN - 0780394046
SN - 9780780394049
T3 - IEEE Workshop on Statistical Signal Processing Proceedings
SP - 727
EP - 732
BT - 2005 IEEE/SP 13th Workshop on Statistical Signal Processing - Book of Abstracts
PB - IEEE Computer Society
T2 - 2005 IEEE/SP 13th Workshop on Statistical Signal Processing
Y2 - 17 July 2005 through 20 July 2005
ER -