Update README.md

README.md

@@ -7,7 +7,7 @@ Also, the credit for this work is not mine alone.  I have several people who are
 To that point, huge thanks to the following people / groups:
 - Chair for System Security @ Ruhr-Universität Bochum / CISPA Helmholtz Center for Information Security
 
-![Alt text](Octave.png?raw=true)
+![Title Picture](Octave.png?raw=true)
 
 
 This project aims to demodulate DJI DroneID frames and eventually be able to craft arbitrary DroneID frames that can be sent with an SDR
@@ -100,7 +100,7 @@ Since there's no change to the order of the symbols, and the 9 OFDM symbol case'
 # Current Questions
 
 ## Cross Correlation
-MATLAB can do a normalized cross correlation using `xcorr(X, Y, 0, 'normalized')` but it's *crazy* slow.  So I wrote my own function ![Alt text](matlab/updated_scripts/normalized_xcorr_fast.m) that is ~ 8x faster than `xcorr` but over 100x slower than the `filter` function that was being used.  If anyone has a better idea on how to do a truly normalized (0.0 - 1.0) cross correlation please let me know.
+MATLAB can do a normalized cross correlation using `xcorr(X, Y, 0, 'normalized')` but it's *crazy* slow.  So I wrote my own function ![normalized_xcorr.m](matlab/updated_scripts/normalized_xcorr_fast.m) that is ~ 8x faster than `xcorr` but over 100x slower than the `filter` function that was being used.  If anyone has a better idea on how to do a truly normalized (0.0 - 1.0) cross correlation please let me know.
 
 ## Burst Extraction
-Right now the normalized cross correlation mentioned above is used to find the bursts using ![Alt text](matlab/updated_scripts/process_file.m).  Since the cross correlation is so slow, a file that contains tens of millions of samples takes a long time in MATLAB and an even longer time in Octave.  The old method of using the `filter` function was blazing fast, but there was no way to know what the correlation thresholds needed to be without making multiple passes through the file.  Energy detection would probably work, but that falls apart in low SNR conditions.  A normalized autocorrelation would likely be as slow as the cross correlation, which probably rules out autocorrelating for the ZC sequence.  I'd love to hear some ideas to help speed this process up.
+Right now the normalized cross correlation mentioned above is used to find the bursts using ![process_file.m](matlab/updated_scripts/process_file.m).  Since the cross correlation is so slow, a file that contains tens of millions of samples takes a long time in MATLAB and an even longer time in Octave.  The old method of using the `filter` function was blazing fast, but there was no way to know what the correlation thresholds needed to be without making multiple passes through the file.  Energy detection would probably work, but that falls apart in low SNR conditions.  A normalized autocorrelation would likely be as slow as the cross correlation, which probably rules out autocorrelating for the ZC sequence.  I'd love to hear some ideas to help speed this process up.