DocumentCode
3482859
Title
Minimum mean-squared error covariance shaping
Author
Eldar, Yonina C.
Author_Institution
Dept. of Electr. Eng., Technion-Israel Inst. of Technol., Haifa, Israel
Volume
6
fYear
2003
fDate
6-10 April 2003
Abstract
The paper develops and explores applications of a linear shaping transformation that minimizes the mean squared error (MSE) between the original and shaped data, i.e., that results in an output vector with the desired covariance that is as close as possible to the input, in an MSE sense. Three applications of minimum MSE shaping are considered, specifically matched filter detection, multiuser detection and linear least-squares parameter estimation.
Keywords
covariance matrices; least mean squares methods; matched filters; minimisation; multiuser detection; parameter estimation; vectors; covariance matrices; data vector covariance; linear least-squares parameter estimation; linear shaping transformation; matched filter detection; minimum mean-squared error covariance shaping; multiuser detection; weighting matrix; Covariance matrix; Detectors; Matched filters; Multiuser detection; Parameter estimation; Process control; Shape control; Spectral shape; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
ISSN
1520-6149
Print_ISBN
0-7803-7663-3
Type
conf
DOI
10.1109/ICASSP.2003.1201781
Filename
1201781
Link To Document