Howtosignalprocessing
- What is the FFT of a square wave?
- What are the limitations of FFT?
- How do you normalize FFT?
- Why is FFT symmetrical?
What is the FFT of a square wave?
In the frequency domain, the overall average of a signal is its content at DC or 0Hz -- so that's why there's a peak at 0Hz. The FFT of a square wave that is centered on 0V has energy at every odd harmonic, starting at 1.
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 normalize FFT?
Normalise the fft by dividing it by the length of the original signal in the time domain. Zero values within the signal are considered to be part of the signal, so 'non-zero samples' is inappropriate. The length to use to normalise the signal is the length before adding zero-padding.
Why is FFT symmetrical?
Because both the positive and negative frequency sinusoids are 90 degrees out of phase and have the same magnitude, they will both respond to real signals in the same way.
