Index: /trunk/MagicSoft/TDAS-Extractor/Calibration.tex
===================================================================
--- /trunk/MagicSoft/TDAS-Extractor/Calibration.tex	(revision 6518)
+++ /trunk/MagicSoft/TDAS-Extractor/Calibration.tex	(revision 6519)
@@ -116,7 +116,7 @@
 \item The reconstructed mean number of photo-electrons lies 4.5 sigma outside 
 the distribution of photo-electrons obtained with the inner or outer pixels in the camera, respectively. 
-This criterium cuts out pixels channels with apparently deviating (hardware) behaviour compared to 
+This criterium cuts out channels with apparently deviating (hardware) behaviour compared to 
 the rest of the camera readout\footnote{This criteria is not applied any more in the standard analysis, 
-although here, we kept using it}.
+although we kept using it here}.
 \item All pixels with reconstructed negative mean signal or with a 
 mean numbers of photo-electrons smaller than one. Pixels with a negative pedestal RMS subtracted 
@@ -128,7 +128,7 @@
 \end{enumerate}
 
-Moreover, the number of events are counted which have been reconstructed outside a 5 sigma region 
+Moreover, the number of events are counted which have been reconstructed outside a 5$\sigma$ region 
 from the mean signal. These events are called ``outliers''. Figure~\ref{fig:outlier} shows a typical 
-outlier obtained with the digital filter applied to a low-gain signal and figure~\ref{fig:unsuited:all}
+outlier obtained with the digital filter applied on a low-gain signal, and figure~\ref{fig:unsuited:all}
 shows the average number of all excluded pixels and outliers obtained from all 19 calibration configurations.
 One can already see that the largest window sizes yield a high number of un-calibrated pixels, mostly 
@@ -162,5 +162,5 @@
 and~\ref{fig:unsuited:23ledsblue} show the resulting numbers of un-calibrated pixels and events for 
 different colours and intensities. Because there is a strong anti-correlation between the number of 
-excluded channels and the number of outliers per event, we have chosen to show these numbers together. 
+excluded pixels and the number of outliers per event, we have chosen to show these numbers together. 
 
 \par
@@ -198,14 +198,13 @@
 One can see that in general, big extraction windows raise the 
 number of un-calibrated pixels and are thus less stable. Especially for the very low-intensity 
-\textit{\bf 1Led\,UV}-pulse, the big extraction windows summing 8 or more slices, cannot calibrate more 
-than 50\% 
-of the inner pixels (fig.~\ref{fig:unsuited:1leduv}). This is an expected behavior since big windows 
-add up more noise which in turn makes the search for the small signal more difficult.
+\textit{\bf 1\,Led\,UV}-pulse, the big extraction windows -- summing 8 or more slices -- cannot calibrate more 
+than 50\% of the inner pixels (fig.~\ref{fig:unsuited:1leduv}). 
+This is an expected behavior since big windows 
+sum up more noise which in turn makes the search for the small signal more difficult.
 \par
 In general, one can also find that all ``sliding window''-algorithms (extractors \#17-32) discard 
 less pixels than the corresponding ``fixed window''-ones (extractors \#1--16). The digital filter with 
 the correct weights (extractors \#30-33) discards the least number of pixels and is also robust against 
-slight modifications of its weights (extractors \#28--30). The robustness gets lost when the high-gain and 
-low-gain weights are inverted (extractors \#31--39, see fig.~\ref{fig:unsuited:23ledsblue}). 
+slight modifications of its weights (extractors \#28--30). 
 \par
 Also the ``spline'' algorithms on small