On estimation of a mixture of normal density functions

1 November 1969

proceedings article
Published by Institute of Electrical and Electronics Engineers (IEEE)

https://doi.org/10.1109/sap.1969.269929

Abstract

A stochastic approximation algorithm is developed for estimating a mixture of normal density functions with unknown means and unknown variances. The algorithm minimizes an information criterion which has interesting properties for density approximations. The question of the completeness of normal density functions for the approximation of the class of continuous probability density functions is analyzed.

Keywords

DENSITY FUNCTIONAL THEORY
STOCHASTIC PROCESSES
PROBABILITY DENSITY FUNCTION
APPROXIMATION ALGORITHMS
DENSITY MEASUREMENT
ALGORITHM DESIGN AND ANALYSIS
DISTRIBUTION FUNCTIONS
EQUATIONS
H INFINITY CONTROL
CONVERGENCE

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