Polynomial expansion of the probability density function about gaussian mixtures
Charles C. Cavalcante, João Mota, João Marcos Travassos Romano · 2005
A polynomial expansion to probability density function (pdf) approximation about Gaussian mixture densities is proposed in this paper. Using known polynomial series expansions we apply the Parzen estimator to derive an orthonormal basis that is able to represent the characteristics of probability distributions that are not concentrated in the vicinity of the mean point such as the Gaussian pdf. The blind source separation problem is used to illustrate the applicability of the proposal in practical analysis of the dynamics of the recovered data pdf estimation. Simulations are carried out to illustrate the analysis