Title :
Online expectation-maximization type algorithms for parameter estimation in general state space models
Author :
Andrieu, Christophe ; Doucet, Amaud
Author_Institution :
Dept. of Math., Bristol Univ., UK
Abstract :
We present new online algorithms to estimate static parameters in nonlinear non-Gaussian state space models. These algorithms rely on online expectation-maximization (EM) type algorithms. Contrary to standard sequential Monte Carlo (SMC) methods recently proposed in the literature, these algorithms do not degenerate over time.
Keywords :
optimisation; parameter estimation; state-space methods; stochastic processes; expectation-maximization type algorithms; general state space models; nonGaussian state space models; nonlinear state space models; online algorithms; sequential Monte Carlo methods; static parameter estimation; stochastic processes; Filtering; Mathematical model; Mathematics; Maximum likelihood estimation; Measurement standards; Monte Carlo methods; Parameter estimation; State estimation; State-space methods; Stochastic processes;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
Print_ISBN :
0-7803-7663-3
DOI :
10.1109/ICASSP.2003.1201620
