Title :
On CRB for Parameter Estimation in Two Component Gaussian Mixtures and the Impact of Misspecification
Author :
Kalyani, Sheetal
fDate :
12/1/2012 12:00:00 AM
Abstract :
A closed form expression for the Cramer Rao lower bound (CRB) for parameter estimation in the presence of a two component Gaussian mixture noise model is derived. It is further shown that this closed form expression can be lower bounded by a simple two term expression. Closed form expressions are also derived for the variance of the maximum likelihood estimator (MLE) when the parameters of the Gaussian mixture model are misspecified. It is then shown that the MLE can handle a significant amount of misspecification of the parameters of the Gaussian mixture model and yet maintain a variance close to the CRB.
Keywords :
Gaussian noise; maximum likelihood estimation; CRB; Cramer Rao lower bound; Gaussian mixture model parameter; Gaussian mixture noise model; MLE; maximum likelihood estimator; parameter estimation; parameter misspecification; Cramer-Rao bounds; Gaussian processes; Gaussian mixtures; Lerch transcendent; Misspecified models; hypergeometric functions;
Journal_Title :
Communications, IEEE Transactions on
DOI :
10.1109/TCOMM.2012.12.110539