New answers tagged dft
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Phase extraction from Fourier transform
You need to evaluate the DFT at the frequency of the input signal.
I recommend doing this experiment with the DTFT instead of the DFT. You can implement it in just a few lines of code, and unless the ...
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FFT of a gaussian signal in Python
There are two issues:
The time axis is not long enough to capture a sufficient length of the Gaussian.
The FFT is not properly scaled.
For the first item mentioned regarding the time axis, the ...
- 36k
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Can anyone explain how dft works as a filter bank?
To add to Richard's good answer, I specifically want to show the difference between:
Down-conversion and low-pass filtering (heterodyne the signal).
Bandpass filtering the signal directly (...
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Can anyone explain how dft works as a filter bank?
@Ahmet. The DFT equation you posted does not compute an array of complex numbers. For any single given integer value of frequency-domain index $k$ the equation tells us how to compute the single ...
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Bandwidth visualization in frequency domain
As a complement to Dan's answer: don't think in terms of the bandwidth per sample; this concept makes no sense.
I recommend studying the discrete-time Fourier transform (DTFT) before the DFT. If you ...
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Bandwidth visualization in frequency domain
The length of the DFT is equal to the length of the time samples used ($N$ samples in time results in $N$ samples in frequency), and this frequency corresponds the the frequency range from $f=0$ to $f=...
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1
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What Does "Reduced Modulo N" mean in this context?
It just means that the number in the double parentheses is changed to be between $0$ and $M-1$ by adding to or subtracting from it $M$ an integer number of times.
See equation (5) of the paper:
$$
\...
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Sparse signal FFT
Partial FFT
Sparse FFT
Can also subsample the input, which will alias (fold) the high frequencies onto lower, then take FFT at the lower length, and then shift the result back onto higher frequencies ...
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