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
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