updating the main page

Author: jeremyfix

README.md

@@ -43,12 +43,16 @@ Each of the script has a line at the beginning giving the compilation line.
 Results
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+TODO: give an order of the speedup
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+
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 Below we plot the comparison of the execution times for performing a linear convolution (the result being of the same size than the source) with various libraries.
 
 ![Comparison of the execution times for linear convolutions](Convolution/PythonScripts/comparison_linear.png)
 
 All these plots show ratio of execution times with a ratio of 1.0 in white. Overall, it is clear that using the FFTW (first line of the plots) library is faster than nested for loops or Octave as soon as the kernel is at least, say, 10 x 10. Overwise, it is better to use nested for loops.
 
-The illustration below is for circular convolution (full, i.e. with a result of size (size source) + (size kernel) - 1)
+The illustration below is for circular convolution (full, i.e. with a result of size (size source) + (size kernel) - 1). Here, it is clear that using the FFTW is much faster, whatever the kernel size.
 
 ![Comparison of the execution times for circular convolutions](Convolution/PythonScripts/comparison_circular.png)