1983
DOI: 10.1109/taes.1983.309451
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Data-Adaptive Detection of a Weak Signal

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Cited by 36 publications
(12 citation statements)
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“…The following cases were looked at: 1) interference plus noise (Hypothesis HO): Dg = D1 + W (16) where D1 is the interference matrix of formula (12) and W is the independent receiver noise matrix of formula (15).…”
Section: Resultsmentioning
confidence: 99%
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“…The following cases were looked at: 1) interference plus noise (Hypothesis HO): Dg = D1 + W (16) where D1 is the interference matrix of formula (12) and W is the independent receiver noise matrix of formula (15).…”
Section: Resultsmentioning
confidence: 99%
“…We shall consider the case of a sum of two 2-D sinusoidal signals observed in no ise y(n,m) = a^^ exp [ j (w n + w 2 m) ] + a-exp [w^n+w^) ] + u(n,m) (1) where n is the time index, n is the space index and u(n,m) are independent noise samples. The method that is being proposed incorporates three different ideas from the work of Nutall [12] (and also Ulrych and Clayton [13]), Jackson and Chien [14] and ours [8] .…”
Section: ) A_2^d Jmen S^on Al_te Chn I Que_for_frequen C Y^w Avenummentioning
confidence: 99%
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“…Recent developments have been influenced by principal component analysis reduced-rank processing principles [18,19]. In this context, the objective is to approximate the orthogonal data processing branch y by an arbitrary "blocking matrix" operator B (L+P )M×(L+P )M (that satisfies B H x = 0) followed by processing by a weighted sum of s < (L + P )M − 1 "dominant" eigenvectors of the blocked-data autocorrelation matrix.…”
Section: Algorithmic Developmentsmentioning
confidence: 99%