A new approach for computing conditional probabilities of general stochastic processes

Proceedings - Simulation Symposium

Volumn 2006, Issue , 2006, Pages 152-159

  Wickborn, Fabian ^a   Isensee, Claudia ^a   Simon, Thomas ^a   Lazarova Molnar, Sanja ^a   Horton, Graham ^a  

^a OTTO VON GUERICKE UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATION THEORY; COMPUTER SIMULATION; PROBABILITY;

BAUM-WELCH-ALGORITHMS; HIDDEN MARKOV MODELS; PROXEL-BASED SIMULATION;

MARKOV PROCESSES;

EID: 33750127661     PISSN: 1080241X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ANSS.2006.7     Document Type: Conference Paper

References (10)

1. L. E. Baum and J. A. Egon. An inequality with applications to statistical estimation of probabilistic functions of a markov process an to a model for ecology. Bull. Amer. Math. Soc., 73:360-363, 1967.
2. L. E. Baum, T. Peterie, G. Souled, and N. Weiss. A maximization technique occurring in the statistical analysis of probabilistic functions of markov chains. Ann. Math. Statist., 41(1):164-171, 1970.
3. L. E. Baum and G. R. Sell. Growth functions for transformation on manifolds. Pac. J. Math., 27(3):211-227, 1968.
4. G. D. Forney. The viterbi algorithm. Proc. IEEE, 61:268-278, March 1973.
5. G. Horton. A new paradigm for the numerical simulation of stochastic petri nets with general firing times. In Proceedings of the European Simulation Symposium 2002. SCS European Publishing House, 2002.
6. C. Isensee and G. Horton. Approximation of discrete phase-type distributions. In ANSS '05: Proceedings of the 38th annual Symposium on Simulation, pages 99-106, Washington, DC, USA, 2005. IEEE Computer Society.
7. M. F. Neuts. Matrix-Geometric Solutions in Stochastic Models: An Algorithmic Approach. The John Hopkins University Press, 1981.
8. L. R. Rabiner. A tutorial on hidden markov models and selected applications in speech recognition. Readings in speech recognition, pages 267-296, 1990.
9. A. H. Viterbi. Error bounds for convolutional codes and an asymptotically optimal decoding algorithm. IEEE Trans. Informat. Theory, IT-13:260-269, April 1967.
10. F. Wickborn and G. Horton. Feasible state space simulation: Variable time steps for the proxel method. In Proceedings of the 2nd Balkan conference in informatics, pages 446-453, Ohrid, Macedonia, November 2005.