Title :
The real-complex normal distribution
Author_Institution :
Dept. of Appl. Phys., Delft Univ. of Technol., Netherlands
fDate :
7/1/1998 12:00:00 AM
Abstract :
An expression is derived for the distribution of a mixture of real and complex normal variates. The asymptotic distribution of the resulting real-complex maximum-likelihood estimates is the real-complex normal distribution derived. The covariance matrix of this distribution is particularly important. It is the asymptotic covariance matrix for maximum-likelihood estimates and the Cramer-Rao lower bound on the variance of the real-complex estimates in general. From this covariance matrix, the variance of the reconstructed complex-valued exit wave then follows using the pertinent propagation formulas. The resulting expressions show the dependence of the variance on the free microscope parameters used for experimental design
Keywords :
covariance matrices; design of experiments; maximum likelihood estimation; normal distribution; signal reconstruction; Cramer-Rao lower bound; asymptotic covariance matrix; asymptotic distribution; experimental design; free microscope parameters; propagation formulas; real-complex maximum-likelihood estimates; real-complex normal distribution; reconstructed complex-valued exit wave; Background noise; Covariance matrix; Gaussian distribution; Gaussian noise; Image reconstruction; Maximum likelihood estimation; Parameter estimation; Statistics; Testing; White noise;
Journal_Title :
Information Theory, IEEE Transactions on