An optimization method for training generalized hidden markov model based on generalized Jensen inequality

ICINCO 2012 - Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics

Volumn 1, Issue , 2012, Pages 268-274

  Hu, Y M ^a   Xie, F Y ^a,b   Wu, B ^a   Cheng, Y ^a   Jia, G F ^a   Wang, Y ^c   Li, M Y ^a  

^a HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b EAST CHINA JIAOTONG UNIVERSITY   (China)

^c GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Generalized baum welch algorithm; Generalized hidden markov model; Generalized jensen inequality

Indexed keywords

ALEATORY UNCERTAINTY; AUXILIARY FUNCTIONS; BAUM-WELCH; BAUM-WELCH ALGORITHMS; CONCAVE FUNCTION; EM ALGORITHMS; ENGINEERING APPLICATIONS; EPISTEMIC UNCERTAINTIES; EXPECTATION MAXIMIZATION; GENERALIZED HIDDEN MARKOV MODELS; GENERALIZED INTERVAL; JENSEN INEQUALITY; LOCAL MAXIMUM; OBJECTIVE FUNCTIONS; OPTIMIZATION METHOD; PROBABILITY MEASURES; TRAINING DATA; TRAINING EQUATIONS; TRAINING PROCESS; UPPER BOUND;

ALGORITHMS; HIDDEN MARKOV MODELS; INFORMATION SCIENCE; PRINCIPAL COMPONENT ANALYSIS; UNCERTAINTY ANALYSIS;

ROBOTICS;

EID: 84867729634     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. Jensen, J. L. W. V., 1906. Sur les functions convexes et les inegalites entre les valeurs moyennes, Acta Math, 30: 175-193.
2. Rabiner, L. R., 1989. A tutorial on hidden Markov models and selected applications in speech recognition, proceedings of the IEEE, 77 (2): 257-286.
3. Kaucher, E., 1980. Interval analysis in the extended interval space IR. Computing Supplement, 2:33-49.
4. Wang, Y., 2011. Multiscale uncertainty quantification based on a generalized hidden Markov model. ASME Journal of Mechanical Design, 3: 1-10.
5. Baum, L. E., Petrie, T, Soules, G., Weiss, Norman., 1970. A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains. Ann. Math. Statist, 41(1): 164-171.
6. Li, X. L., Parizeau, M., Plamondon, R., 2000. Training hidden Markov models with multiple observations - A vombinatorial method. IEEE Transactions on PAMI, (22)4: 371-377.
7. Popova, E. D., 2000. All about generalized interval distributive relations. I. Complete Proof of the Relations Sofia.
8. Gardenes, E., Sainz, M. A., Jorba, L., Calm, R., Estela, R., Mielgo, H. and Trepat, A., 2001. Modal intervals. Reliable Computing, 2: 77-111.
9. Markov, S., 1979. Calculus for interval functions of a real variable Computing, 22(4): 325-337.
10. Levinson, S., Rabiner, R. and Sondhi, M., 1983. An introduction to the application of the theory of probabilistic functions of a Markov process to automatic speech recognition. Bell Systems Technical Journal, 62: 1035-1074.