Abstract:

The mixture of factor analyzers(MFA)can accurately
describe high resolution range profile(HRRP)statistical charac-
teristics.But how to determine the proper number of the models
is a problem.This paper develops a variational Bayesian mixture
of factor analyzers(VBMFA)model.This procedure can obtain a
lower bound on the Bayesian integral using the Jensen’s inequality.
An analytical solution of the Bayesian integral could be obtained
by a hypothesis that latent variables in the model are indepen-
dent.During computing the parameters of the model,birth-death
moves are utilized to determine the optimal number of model au-
tomatically.Experimental results for measured data show that the
VBMFA method has better recognition performance than FA and
MFA method.