Hi All,(adsbygoogle = window.adsbygoogle || []).push({});

I have a problem I've been thinking about for a while, but I haven't come up with a really satisfactory solution:

I want to do a discrete fourier transform on data that has been sampled at 2 different sampling frequencies. I've attached a picture of what my data will look like. The goal with these two different sampling rates is to use a long waveform for good resolution in the fourier transform (be able to see low frequencies), and also use high sample rate to see the high frequencies in the data.

I've considered averaging the high-sampled data and doing a fast fourier transform (FFT) on that, and then also doing another independent FFT of the higher-sample-rate data, and then stitching these FFTs together. The problem is that will give me different resolutions of the FFTs, and I believe also cause some unorthodox aliasing issues.

Any suggestions/references would be greatly appreciated,

Cheers!

(I'm familiar with Fourier-transforms for non-uniformly sampled data, (such as the Lomb-Scargle method) but I'm hoping for a simpler solution since my data won't be completely non-uniform, but just at two different frequencies.)

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# Discrete fourier transform data of 2 different sampling frequencies

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