Title | Offline and online identification of hidden semi-Markov models |
Publication Type | Journal Article |
Year of Publication | 2005 |
Authors | Azimi, M., P. Nasiopoulos, and R. K. Ward |
Journal | Signal Processing, IEEE Transactions on |
Volume | 53 |
Pagination | 2658 - 2663 |
Date Published | aug. |
ISSN | 1053-587X |
Keywords | adaptive algorithm, expectation maximization algorithm, hidden, hidden Markov models, offline identification, online identification, parameter identification algorithm, probability, recursive error prediction, recursive estimation, recursive maximum likelihood, semiMarkov model, signal processing, state-duration-dependant transition probability |
Abstract | We present a new signal model for hidden semi-Markov models (HSMMs). Instead of constant transition probabilities used in existing models, we use state-duration-dependant transition probabilities. We show that our modeling approach leads to easy and efficient implementation of parameter identification algorithms. Then, we present a variant of the EM algorithm and an adaptive algorithm for parameter identification of HSMMs in the offline and online cases, respectively. |
URL | http://dx.doi.org/10.1109/TSP.2005.850344 |
DOI | 10.1109/TSP.2005.850344 |