deletions | additions       diff --git a/results_sensitivity.md b/results_sensitivity.md  index a3cb3fe..decf2ec 100644  --- a/results_sensitivity.md  +++ b/results_sensitivity.md 
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\[  SNR = \frac{\frac{1}{b-a}{\int_a^b f(t)^2\,dt}}{\sigma_n^2}  \]  where *a* and *b* are times, before and after the peak respectively, when the fluorescence is at half of its peak value (i.e., b-a *b-a*  is FDHM), *f(t)* is the event signal and \(\sigma_n\) the standard deviation of the noise. The resulting plot is depicted on figure x, and it can be seen that detection probability is only dependent on the *SNR*. For visual comparison, the appearance of 4 events with different *SNR* and detection probabilities are shown on Figure x.  The  accuracy of the fit is calculated as the average square difference between the fit and the original clean signal. It is presented as a percentage of the maximal error which is obtained when no event regions are detected and the entire signal is fitted with just the baseline function. Since the baseline function is a fourth order polynomial it can fit the signal to some degree (e.g., the \(R^2\) value of the fit is 0.41 for the example in Figure x). Therefore Curves calculated for different amplitudes overlap when plotted as a function of *SNR*.  ###Release event detection