Howtosignalprocessing
- How many points do you need for FFT?
- How can I make my FFT more accurate?
- How many samples do I need for FFT?
- How does sample rate affect FFT?
How many points do you need for FFT?
Because the FFT function uses a base 2 logarithm by definition, it requires that the range or length of the time series to be evaluated contains a total number of data points precisely equal to a 2-to-the-nth-power number (e.g., 512, 1024, 2048, etc.).
How can I make my FFT more accurate?
The most intuitive way to increase the frequency resolution of an FFT is to increase the size while keeping the sampling frequency constant. Doing this will increase the number of frequency bins that are created, decreasing the frequency difference between each.
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 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.
