TY - GEN
T1 - Prequential Bayes mixture approach for Gaussian mixture order selection
AU - Gilbert, K.
AU - Bilik, I.
AU - Buck, J.
AU - Payton, K.
PY - 2010/12/20
Y1 - 2010/12/20
N2 - This paper presents a modified prequential Bayes (MPB) method for model order estimation of Gaussian mixture models (GMM). The proposed MPB order estimators recursively update the weighting for each order in a class of model orders from the mixture of a time-invariant prior and the likelihood of the observed data for each model. This paper investigates both a maximum a posteriori (MAP) switching version and an affine version of the MPB order estimator. Simulations demonstrate that the proposed MPB estimators are more accurate for small sample sizes than the minimum description length (MDL) criterion and the Akaike information criterion (AIC).
AB - This paper presents a modified prequential Bayes (MPB) method for model order estimation of Gaussian mixture models (GMM). The proposed MPB order estimators recursively update the weighting for each order in a class of model orders from the mixture of a time-invariant prior and the likelihood of the observed data for each model. This paper investigates both a maximum a posteriori (MAP) switching version and an affine version of the MPB order estimator. Simulations demonstrate that the proposed MPB estimators are more accurate for small sample sizes than the minimum description length (MDL) criterion and the Akaike information criterion (AIC).
UR - http://www.scopus.com/inward/record.url?scp=78650161740&partnerID=8YFLogxK
U2 - 10.1109/SAM.2010.5606729
DO - 10.1109/SAM.2010.5606729
M3 - Conference contribution
AN - SCOPUS:78650161740
SN - 9781424489770
T3 - 2010 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2010
SP - 173
EP - 176
BT - 2010 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2010
T2 - 2010 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2010
Y2 - 4 October 2010 through 7 October 2010
ER -