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Optimal linear correction in LMMSE estimation using moments of the complex inverse Wishart distribution

Author
Serra, J.; Najar, M.
Type of activity
Presentation of work at congresses
Name of edition
2012 IEEE Statistical Signal Processing Workshop
Date of publication
2012
Presentation's date
2012
Book of congress proceedings
2012 IEEE Statistical Signal Processing Workshop (SSP 2012): Ann Arbor, Michigan, USA: 5-8 August, 2012
First page
872
Last page
875
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
DOI
https://doi.org/10.1109/SSP.2012.6319846 Open in new window
Repository
http://hdl.handle.net/2117/19330 Open in new window
URL
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6319846 Open in new window
Abstract
The conventional linear minimum mean square error esti- mator (LMMSE) suffers a severe performance degradation whenever the sample size is comparable to the observation dimension. In order to tackle this problem, we propose an optimal linear correction of the conventional LMMSE, which minimizes the average mean square error (MSE) by using the moments of the complex inverse Wishart distribution. Numerical simulations highlight that the proposed estimator dramatically outperforms the conventional ...
Citation
Serra, J.; Najar, M. Optimal linear correction in LMMSE estimation using moments of the complex inverse Wishart distribution. A: IEEE Statistical Signal Processing Workshop. "2012 IEEE Statistical Signal Processing Workshop (SSP 2012): Ann Arbor, Michigan, USA: 5-8 August, 2012". Ann Arbor, Michigan: Institute of Electrical and Electronics Engineers (IEEE), 2012, p. 872-875.
Keywords
Complex Inverse Wishart, LMMSE, Shrinkage, Small sample size
Group of research
A&MP - Array and Multichannel Processing Group

Participants