Howtosignalprocessing
- How many samples do I need for FFT?
- How do you find the FFT of a signal?
- How does sample rate affect FFT?
- How do you get your FFT size?
How many samples do I need for FFT?
The number of samples (N) in the FFT must be an integer power of 2. Therefore, N = 2p, where p is a positive integer. This rule minimizes the number of multiplications—and therefore the computation time—needed to compute the coefficients of the Fourier series.
How do you find the FFT of a signal?
y = fft(x); fs = 1/Ts; f = (0:length(y)-1)*fs/length(y); When you plot the magnitude of the signal as a function of frequency, the spikes in magnitude correspond to the signal's frequency components of 15 Hz and 20 Hz.
How does sample rate affect FFT?
The amplitude of the DFT (FFT) is proportional to the number of samples. Therefore, if you sample for twice as long at the same sampling frequency, or if you sample for the same duraiton but twice as fast, you will have twice as many data points, and the DFT amplitude will be twice as large. See examples below.
How do you get your FFT size?
The FFT size defines the number of bins used for dividing the window into equal strips, or bins. Hence, a bin is a spectrum sample , and defines the frequency resolution of the window. By default : N (Bins) = FFT Size/2.
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