FFT of Downsampled Signal
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I have an aperoidic signal that is being sampled at a very high frequency, 3.125 MHz. The signal is sampled for 8 minutes, leaving me with a very large dataset to process (1.3E9 samples). Moreover, I am confident that the data is being oversampled by a large factor so I believe that I can downsample it by a factor of ten. I am chosing to downsample primarily because of computational limits.
Would I best use downsample() or decimate()?
And the real question: How would downsampling/decimating the data by an order of 10 affect the FFT? I would like to have a meaningful frequency axis in the power-spectrum-density plot. Would I just treat my sample frequency as fs/10, 312.5 KHz?
Thanks for any guidance.
Greg Dionne on 30 Apr 2019
If you have significant noise on the signal, then decimate(x,10) or resample(x,1,10) would be preferable. Your resulting sample rate is as you have indicated (312.5 kHz).
I would take a spectrogram on the resulting signal to see how the frequency content changes over time.
Hope this helps!