ISSN:
1573-1375
Keywords:
EM algorithm
;
deconvolution
;
linear filters
;
stochastic algorithms
;
simulated annealing
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
,
Mathematics
Notes:
Abstract The Expectation–Maximization (EM) algorithm is a very popular technique for maximum likelihood estimation in incomplete data models. When the expectation step cannot be performed in closed form, a stochastic approximation of EM (SAEM) can be used. Under very general conditions, the authors have shown that the attractive stationary points of the SAEM algorithm correspond to the global and local maxima of the observed likelihood. In order to avoid convergence towards a local maxima, a simulated annealing version of SAEM is proposed. An illustrative application to the convolution model for estimating the coefficients of the filter is given.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1018594320699
Permalink