Title :
Design of minimum MSE detection matrix filters
Author :
Rizq, Nader N. ; Lindquist, Claude S.
Author_Institution :
Gables Engineering Inc., Coral Gables, FL, USA
Abstract :
The square matrix system representation is used to derive matched, high-resolution and inverse detection matrix filters using gradient maximization. The results are identical to those derived using the Schwarz inequality maximization method. A unifying result that portrays detection square matrix systems as minimum mean square error systems is presented. Historically, minimum mean square error systems have been associated with estimation and correlation type algorithms
Keywords :
filtering and prediction theory; least squares approximations; matrix algebra; signal detection; detection square matrix systems; gradient maximization; high-resolution; inverse detection matrix filters; matched filters; minimum MSE detection matrix filters; minimum mean square error systems; Equations; Filtering; Frequency domain analysis; Linear matrix inequalities; Matched filters; PSNR; Signal design; Signal resolution; Signal to noise ratio; Transfer functions;
Conference_Titel :
Signals, Systems and Computers, 1992. 1992 Conference Record of The Twenty-Sixth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-3160-0
DOI :
10.1109/ACSSC.1992.269201
