I have a program which takes in data from an oscilloscope, and due to reflections in the medium, we will get random signals at random intervals. The two grey windows at the right bottom show the original data (below red line), and after FFT forward and backward (above red line).
The data set is originally 10,000 points, so the FFT has 20000 doubles stored. You can see in the command shell that the backwards FFT uses 19000 of those 20000 values. My issue is at the green rectangle I get waves before and after the real signal, which means I can hardly denoise it due to the signal itself being a rather sharp and high frequency.
Would I first find and extract the areas where the signal itself is present, and then run the FFT on that subset, or how would I go with denoising such an area?
The noise itself is not visible, since the 10k data points are scaled to 500 pixel, but its random electric noise coming from the oscilloscope.
Link to the image in big: http://i.imgur.com/3fHo8vP.png
The other two images show the similar data being captured, once being averaged 128 times, one a single set. I need to find a way to denoise the single capture.