Wael AbdAlmageed

Non-parametric expectation maximization: a learning automata approach

TitleNon-parametric expectation maximization: a learning automata approach
Publication TypeConference Paper
Year of Publication2003
AuthorsW. Abd-almageed, A. El-Osery, and C. E. Smith
Conference NameIEEE International Conference on Systems Man and Cybernetics
Date PublishedOct
Abstract

The famous expectation maximization technique suffers two major drawbacks. First, the number of components has to be specified apriori. Also, the expectation maximization is sensitive to initialization. In this paper, we present a new stochastic technique for estimating the mixture parameters. Parzen Window is used to estimate a discrete estimate of the PDF of the given data. Stochastic learning automata is then used to select the mixture parameters that minimize the distance between the discrete estimate of the PDF and the estimate of the expectation maximization. The validity of the proposed approach is verified using bivariate simulation data.

Groups: