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The Test Statistic of the Two Sample Locally Optimum Rank Detector for Random Signals in Weakly Dependent Noise Models  

Bae, Jin-Soo (세종대학교 정보통신공학과)
Abstract
In this paper, the two sample locally optimum rank detector is obtained in the weakly dependent noise with non-zero temporal correlation between noise observations. The test statistic of the locally optimum rank detector is derived from the Neyman-Pearson lemma suitable for the two sample observation models, where it is assumed that reference observations are available in addition to regular observations. Two-sample locally optimum rank detecter shows the same performance with the one-sample locally optimum rank detector asymptotically. The structure of the two-sample rank detector is simpler than that of the one-sample rank detector because the sign statistic is not processed separately.
Keywords
Two Sample; Locally Optimum; Reference Observations; Test Statistic; Weakly Dependent Noise Model;
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