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How does the sample rate work on an SDR?

One way to do this is bandpass sampling or undersampling. I've copied the text below from an answer I wrote to a slightly different question. Here, to avoid aliasing distortion, the signal of ...
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How does the sample rate work on an SDR?

There are a few different ways to do this: Frequency shifting via multiplying (frequency mixing): Multiplying a signal by a sine wave of a specific frequency produces a new signal which is shifted ...
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How to Calculate Frequency "X values" from a FFT/DFT Transformation

What you have heard about the sampling frequency/rate and the number of samples/data points is correct. When you take $n$ samples in the time-domain representation of the signal and "Fourier ...
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Sampling and Aliasing

I think the main take away of this whole section is If you sample a signal in time it becomes periodic in frequency Let's look at an example: A sinusoidal signal with a frequency of $f = 1Hz$ ...
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Optimum sampling frequency for decoding analog PDM stream?

uniform-time ADC-based sampling of PDM no matter how fast you could sample, your ADC needs an analog anti-aliasing filter. That's the key here: Your AA filtering inherently "sums up" the ...
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Optimum sampling frequency for decoding analog PDM stream?

I'm not familiar with PDM, but the rule of sampling in general is to have a sample rate at least twice faster as the maximum frequency of the signal want to digitalize Nyquist-Shannon Theorem to have ...
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What is the frequency representation of nonuniform sampling?

Matlab has the nufft which uses: For a vector $X$ of length $n$, sample points $t$, and frequencies $f$, the nonuniform discrete Fourier transform of $X$ is ...
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What is the frequency representation of nonuniform sampling?

If the samples are finite (e.g. not a running process) then you'd have to take the greatest common divider and resample all the vector, resulting in a "toothless" train of impulses. For ...
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What is the frequency representation of nonuniform sampling?

For the simplest case of $N$ random samples of $x(t)$ taken over a duration of $T$ and satisfying the average Nyquist rate criterion, then the resulting Fourier transform of the non-uniform samples ...
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MFCC window size at different sampling rates

Smaller durations are better because they increase the time resolution. What would be the reason to still prefer 40 msec over 20 msec? Larger samples are better because they increase the frequency ...
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Quadrature Detector with a single ADC

The sampling offset is a time delay between the I and Q paths. The Fourier Transform of a time delay $T$ is $e^{-j\omega T}$ and thus we see that this will impart a linear phase that is proportional ...
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Quadrature Detector with a single ADC

If you are sampling at 24kHz and each of I and Q are be limited to 4kHz, the effect of one sample offset should be limited. If you want to reduce it further, perhaps you could do a simple linear ...
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FFT to work out optimum number of samples to average

When you take many samples and calculate an FFT, you likely find that noise is flat in the higher portion of the spectrum and for lower frequencies eventually noise will rise proportional to √f or ...
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FFT to work out optimum number of samples to average

The optimum number of samples to average over for any series of data which may become non-stationary over longer time intervals is readily determined by using the "Allan Deviation" (ADEV) ...
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