DocumentCode :
922785
Title :
An RKHS approach to detection and estimation problems--II: Gaussian signal detection
Author :
Kailath, Thomas ; Weinert, Howard L.
Volume :
21
Issue :
1
fYear :
1975
fDate :
1/1/1975 12:00:00 AM
Firstpage :
15
Lastpage :
23
Abstract :
The theory of reproducing kernel Hilbert spaces is used to obtain a simple but formal expression for the likelihood ratio (LR) for discriminating between two Gaussian processes with unequal covariances, and to develop a test by which the formal expression can be checked for validity. This LR formula can be evaluated by working separately with each covariance, thus reducing the calculations for the random signal case to those for the simpler known signal problem. In contrast, all previous LR formulas for the unequal covariance problem seem to require calculations involving both covariances simultaneously.
Keywords :
Gaussian processes; Hilbert spaces; Signal detection; Signal estimation; Eigenvalues and eigenfunctions; Gaussian noise; Gaussian processes; Hilbert space; Integral equations; Kernel; Laboratories; Signal detection; Signal to noise ratio; Testing;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.1975.1055328
Filename :
1055328
Link To Document :
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