103 search results - page 1 / 21 » An EM Algorithm for Nonlinear State Estimation With Model Un... |
TSP
2008
13 years 5 months ago
2008
NIPS
1998
13 years 6 months ago
1998
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
ICANN
2009
Springer
13 years 10 months ago
2009
Springer
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
CSDA
2007
13 years 5 months ago
2007
Nonlinear random effects models with finite mixture structures are used to identify polymorphism in pharmacokinetic/ pharmacodynamic (PK/PD) phenotypes. An EM algorithm for maxim...
ICIP
2001
IEEE
14 years 7 months ago
2001
IEEE
The HMM (Hidden Markov Model) is a probabilistic model of the joint probability of a collection of random variables with both observations and states. The GMM (Gaussian Mixture Mo...