Estimation of mixture densities from histograms [signal classification]

Many signals and statistical distributions are a mixture of component signals or distributions. Current methods for estimating the proportion of each component assume a parametric form for the components. We introduce nonparametric methods, based on projections onto convex sets, to address the many practical cases where parametric models are not applicable. Comparisons are made with parametric methods and discussed for special cases where both methods can be used.