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Dec 5, 2023 at 19:19 history edited robert bristow-johnson CC BY-SA 4.0
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Dec 5, 2023 at 13:33 comment added robert bristow-johnson The $\operatorname{sinc}^2 \left( \frac{f}{f_\mathrm{s}} \right)$ will cause some rolloff in the high end. Now, if you want to compensate for that with a little boost in your pre-LPF before it cuts off, that might be good. For a biquad LPF it's a $Q > \sqrt{\frac12}$ that will put a little bump up there. But your main problem might become aliasing if there is content in your original signal that is close to Nyquist. That content will alias. The rolloff of linear interpolation is down by -7.8448 dB at Nyquist.
Dec 5, 2023 at 11:27 comment added hajo I am thinking of how my spectrum will look like after all. Sampling my bandpass signal with fs will replicate the image of the spectrum every k*fs. Now I am trying to interpolate the values between the samples which will lead the spectrum to a multiplication with sinc^2(f/fs) creating zeros of my replicated image.
Dec 5, 2023 at 0:11 comment added robert bristow-johnson The aliasing happens because the images (images are not the same as aliases) are not completely killed by the implied LPF that occurs when your interpolating. What survives of those images can then fold back into your baseband whenever the resampling frequency is different than the original sample rate. It doesn't matter whether the resampling frequency is little greater or a little less than the original. It's because it's different and that your images are not completely dead zero.
Dec 4, 2023 at 23:56 comment added hajo Thank you to the answer. I have following questions: -Is in my case aliasing produced because we are resampling at a frequency less than double the nyquist frequency? -Do you mean by sample rate the original one or the sample rate after resampling (samples+resamples)
Dec 4, 2023 at 22:27 history edited robert bristow-johnson CC BY-SA 4.0
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Dec 4, 2023 at 22:19 history answered robert bristow-johnson CC BY-SA 4.0