- What are the limitations of FFT?
- How do you overcome the limitation of a Fourier transform?
- How can I make my FFT more accurate?
What are the limitations of FFT?
A disadvantage associated with the FFT is the restricted range of waveform data that can be transformed and the need to apply a window weighting function (to be defined) to the waveform to compensate for spectral leakage (also to be defined). An alternative to the FFT is the discrete Fourier transform (DFT).
How do you overcome the limitation of a Fourier transform?
The solution to this is time-frequency analysis, which is a field that deals with signal processing in both time and frequency domain.
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.