I have a discrete signal sampled @Fs. I need to downsample it to Fs/k. Main reason is to reduce signal bandwidth and speed up computation : I'm only interested in a reduced bandwidth < Fs/2k. Some high frequency noise >> Fs/2k can exist : antialiasing is needed. From what I understand, I have several options :
- brute force : decimation (without taking care of aliasing problem!)
- antialiasing + decimation : I can use for example numpy decimate function
- frequency approach : FFT then truncation then IFFT, can be done using resample
Only solution 2- 3- help solving antialiasing issue. 3- filters in frequency domain, supposing signal is periodic. 2- filters with IIR/FIR filter.
I can always use decimate without questioning, but I would like to precisely understand limitations behind. What are drawbacks / advantages of using solution 2- versus 3-? Do you have some practical guidelines about downsampling? Some recommendations?
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