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MLP-based approximation to the Neyman Pearson detector in a terrestrial passive bistatic radar scenario.

, , , , and . EUROCON, page 1-6. IEEE, (2015)

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Improving neural classifiers for ATR using a kernel method for generating synthetic training sets., , , and . NNSP, page 425-434. IEEE, (2002)Approximating the Neyman-Pearson Detector for Swerling I Targets with Low Complexity Neural Networks., , , , and . ICANN (2), volume 3697 of Lecture Notes in Computer Science, page 917-922. Springer, (2005)Estimation of ocean wave heights from temporal sequences of X-Band marine radar images., , , and . EUSIPCO, page 1-5. IEEE, (2006)Doppler Processors as Suboptimum Approaches for Detecting Targets with Unknown Doppler Shift., , , , and . CICSyN, page 283-288. IEEE, (2013)Time-frequency analysis as a tool for improving neural detectors for low probability of false alarm., , , and . ICECS, page 91-94. IEEE, (2001)Enlarging Training Sets for Neural Networks., , , and . ANNs, page 25-33. INSTICC Press, (2004)On the Capability of Neural Networks to Approximate the Neyman-Pearson Detector: A Theoretical Study., , , and . ANNs, page 69-76. INSTICC Press, (2004)SONN and MLP Based Solutions for Detecting Fluctuating Targets with Unknown Doppler Shift in Gaussian Interference., , , , and . IWANN (1), volume 7902 of Lecture Notes in Computer Science, page 584-591. Springer, (2013)Using Multilayer Perceptrons to Align High Range Resolution Radar Signals., , , and . ICANN (2), volume 3697 of Lecture Notes in Computer Science, page 911-916. Springer, (2005)MLP and RBFN for Detecting White Gaussian Signals in White Gaussian Interference., , , and . IWANN (2), volume 2687 of Lecture Notes in Computer Science, page 790-797. Springer, (2003)