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| 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 |