M. Lavielle et D. Marquez, Gibbs sampling for parameters estimation and change-points detection in inverse problems. Application to electromagnetic imaging, SIGNAL PROC, 78(3), 1999, pp. 349-362
In the framework of Bayesian inverse problems, we investigate the use of su
itable prior probabilities for modeling the presence of abrupt changes in t
he distribution of the non-observed data sequence. We adopt a Gibbs-type sa
mpling method for estimating the posterior distribution of this sequence. I
n the second part, we apply recent results on stochastic versions of the we
ll-known EM algorithm with averaging and acceleration techniques, to estima
te some parameters of the model. A numerical example for the magnetotelluri
c inverse problem is proposed. (C) 1999 Elsevier Science B.V. All rights re
served.