Title :
Estimation of the Parameters of a Gaussian Mixture Using the Method of Moments
Author :
Fukunaga, Keinosuke ; Flick, Thomas E.
Author_Institution :
FELLOW, IEEE, School of Electrical Engineering, Purdue University, West Lafayette, IN 47907.
fDate :
7/1/1983 12:00:00 AM
Abstract :
Given a general n-dimensional bimodal Gaussian mixture, this paper shows how unknown parameters may be found by the method of moments. Three cases are considered-equal modal probabilities, known but not necessarily equal probabilities, and all parameters unknown. The solution involves sample moments no higher than fourth order. For Gaussian mixtures where the number of modes is unknown, fourth-order moments can be used to count them, provided all modes have the same covariance matrix, and their multiplicity is not greater than data dimensionality. Examples of mode-counting and the determination of bimodal parameters are included.
Keywords :
Approximation algorithms; Convergence; Covariance matrix; Detectors; Equations; Laboratories; Maximum likelihood detection; Moment methods; Parameter estimation; Stochastic processes; Bimodal Gaussian mixture; kurtosis matrix; method of moments; mode-counting; parameter evaluation; semi-absolute moments; third- and fourth-order moments;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1983.4767410