Impact of STFT window function and FFT length on computation time

1. How does window length affect spectrogram?
2. What is the difference between FFT and STFT?
3. Why do we use windowing when working with FFTs?
4. Which time window weighting function is most appropriate for amplitude accuracy and calibration of a continuous time signal?

How does window length affect spectrogram?

However, since spectrogram has a fix window size, there exists a dilemma of resolution, where the too narrow window will result in a poor frequency resolution, and a too wide window will cause poor time resolution.

What is the difference between FFT and STFT?

FFT has a resolution of 2048 lines, Blackman window, and 50% overlap and STFT also has Block size 2048, FFT size 16K, Blackman window used, and 50% overlap. As we can see, STFT performs better with the same block size (but more calculated lines). We improved frequency resolution for the same amount of scooped data.

Why do we use windowing when working with FFTs?

You can minimize the effects of performing an FFT over a noninteger number of cycles by using a technique called windowing. Windowing reduces the amplitude of the discontinuities at the boundaries of each finite sequence acquired by the digitizer.

Which time window weighting function is most appropriate for amplitude accuracy and calibration of a continuous time signal?

Hanning is the most commonly used window function for random signals because it provides good frequency resolution and leakage protection with fair amplitude accuracy.