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Increasing the ERP signal in the detection of guilty knowledge

✍ Scribed by Theron E. Parsons; Michael Surrette; Richard L. Marsh

Publisher
Springer-Verlag
Year
2000
Tongue
English
Weight
683 KB
Volume
15
Category
Article
ISSN
0882-0783

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The fuzzy constant false alarm rate (CFAR) detector, which is based on the M -out-of-N binary detector, is characterized and compared with the optimal Neyman -Pearson detector. It replaces the crisp M -out-of-N binary threshold with a soft, continuous threshold, implemented as a membership function.