Title :
An EM algorithm for singular state space models: II
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
Abstract :
For pt.I see ibid. (2003). We develop a state space EM algorithm for the case when the state innovations covariance matrix is singular and where there is correlation between state and observation noise. Previous state space EM algorithms precluded this practically important case.
Keywords :
covariance matrices; maximum likelihood estimation; optimisation; state-space methods; EM algorithm; expectation maximization algorithm; maximum likelihood parameter estimator; observation noise; singular state innovations covariance matrix; singular state space models; state noise; Convergence; Covariance matrix; Gaussian noise; Maximum likelihood estimation; Parameter estimation; Perturbation methods; State-space methods; Technological innovation; White noise; Yttrium;
Conference_Titel :
Decision and Control, 2004. CDC. 43rd IEEE Conference on
Print_ISBN :
0-7803-8682-5
DOI :
10.1109/CDC.2004.1429288
