A gradient BYY harmony learning rule on Gaussian mixture with automated model selection

One important feature of Bayesian Ying–Yang (BYY) harmony learning is that model selection can be made automatically during parametric learning. In this paper, BYY harmony learning with a bi-directional architecture is studied for Gaussian mixture modelling via a gradient learning rule. It has been demonstrated by simulation experiments that the number of Gaussians can be determined automatically during learning the parameters of the Gaussian mixture. c © 2003 Published by Elsevier B.V.