Adaptive threshold estimation via extreme value theory
IEEE Transactions on Signal Processing
Rejection threshold estimation for an unknown language model in an OCR task
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
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The problem of detecting radar signals embedded in clutter is an area of great interest. In many radar applications, it is important to set thresholds to achieve a false alarm probability (PF) of 10-5 or lower. Using conventional Monte Carlo techniques, where thresholds are set based on raw percentiles, an extremely large number of samples is required. We use the generalized Pareto distribution to approximate the extreme tail of the distributions and propose the ordered sample least squares (OSLS) method for estimating its parameters