DocumentCode
2184550
Title
Improved smoother dynamics for discrete time HMM parameter estimation
Author
Elliott, R.J. ; Malcolm, W.P.
Author_Institution
Fac. of Manage., Calgary Univ., Alta., Canada
Volume
4
fYear
2001
fDate
2001
Firstpage
3506
Abstract
In this article, we consider hidden Markov model (HMM) parameter estimation in the context of an expectation maximisation (EM) algorithm. The models we study are discrete-time Markov chains observed in Gaussian noise. New formulae for updating smoothed estimates are given for the models just described. These formulae are computed by exploiting a duality between a forward-in-time unnormalised probability process and its dual
Keywords
Gaussian noise; discrete time filters; duality (mathematics); hidden Markov models; optimisation; parameter estimation; probability; smoothing methods; Gaussian noise; discrete-time HMM parameter estimation; discrete-time Markov chains; duality; expectation maximisation algorithm; forward-in-time unnormalised probability process; hidden Markov model; martingales; reference probability; smoothed estimate updating; smoother dynamics; Books; Boundary conditions; Equations; Gaussian noise; Glands; Hidden Markov models; Mathematics; Noise robustness; Parameter estimation; Random variables;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 2001. Proceedings of the 40th IEEE Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-7061-9
Type
conf
DOI
10.1109/.2001.980402
Filename
980402
Link To Document