@shinmera oh, I'm aware people have done what you're saying in particular, but I've never watched such a thing. Basically you do a discrete convolution/correlation of two arrays, the test sample, and the kernel. We expect that bins in the result exceeding some sensitivity number you choose by trial and error are detections of the kernel in the test sample. You judge your quality by the True Positive Fraction and False Positive Fraction for your chosen sensitivity.