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The theory of the -interval partition detector is extended to include the analysis and design of nonconstant signals. Using the derived locally most powerful scores, the performance of this detector is investigated. A discrete formulation is used to select the signal and correlation function of the detector to optimize a performance index that reflects the system constraints. Though the detector appears to be similar to a conventional correlation detector, it retains the robustness properties of the -interval detector. In addition, a method is presented whereby dependent samples may be used while still retaining nonparametric operation of the detector.