DocumentCode
1787763
Title
Naive, robust or fully-adaptive: An estimation problem for CES distributions
Author
Greco, Maria S. ; Fortunati, Stefano ; Gini, F.
Author_Institution
Dept. of Inf. Eng., Univ. of Pisa, Pisa, Italy
fYear
2014
fDate
22-25 June 2014
Firstpage
457
Lastpage
460
Abstract
In this paper we deal with the estimation of the covariance matrix for Complex Elliptically Symmetric (CES) data. We follow three different approaches with different level of knowledge on the specific CES model and we compare the asymptotic performances under the three approaches in terms of Cramér-Rao Bounds and Huber limit.
Keywords
adaptive estimation; adaptive signal processing; covariance matrices; CES data distribution; Cramér-Rao bound; Huber limit; adaptive estimation; adaptive signal processing; complex elliptically symmetric data distribution; covariance matrix estimation; Covariance matrices; Data models; Distributed databases; Maximum likelihood estimation; Robustness; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Sensor Array and Multichannel Signal Processing Workshop (SAM), 2014 IEEE 8th
Conference_Location
A Coruna
Type
conf
DOI
10.1109/SAM.2014.6882441
Filename
6882441
Link To Document