Title :
A Complex Generalized Gaussian Distribution— Characterization, Generation, and Estimation
Author :
Novey, Mike ; Adali, Tülay ; Roy, Anindya
Author_Institution :
Univ. of Maryland Baltimore County, Catonsville, MD, USA
fDate :
3/1/2010 12:00:00 AM
Abstract :
The generalized Gaussian distribution (GGD) provides a flexible and suitable tool for data modeling and simulation, however the characterization of the complex-valued GGD, in particular generation of samples from a complex GGD have not been well defined in the literature. In this correspondence, we provide a thorough presentation of the complex-valued GGD by: (i) constructing the probability density function (pdf); (ii) defining a procedure for generating random numbers from the complex-valued GGD; and (iii) implementing a maximum likelihood estimation (MLE) procedure for the shape and covariance parameters in the complex domain. We quantify the performance of the MLE with simulations and actual radar data.
Keywords :
Gaussian distribution; maximum likelihood estimation; signal processing; complex-valued generalized Gaussian distribution; complex-valued signal processing; covariance parameters; data modeling; maximum likelihood estimation procedure; probability density function; radar data; shape parameters; Complex-valued signal processing; generalized Gaussian distribution (GGD); maximum likelihood estimation (MLE);
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2009.2036049