Classifying STFT from multiple signal samples

1. What is the difference between STFT and wavelet transform?
2. How do you calculate short-time Fourier transform?
3. What is the difference between FFT and STFT?
4. What is STFT spectrogram?

What is the difference between STFT and wavelet transform?

In contrast to the standard STFT which uses a single window size, the wavelet transform (WT) uses short windows at high frequencies and long windows at low frequencies [21]. Wavelets rely on the use of a mother wavelet function that can be scaled and shifted, to correlate with the anomalies or events of the signals.

How do you calculate short-time Fourier transform?

In practice, the procedure for computing STFTs is to divide a longer time signal into shorter segments of equal length and then compute the Fourier transform separately on each shorter segment. This reveals the Fourier spectrum on each shorter segment.

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.

What is STFT spectrogram?

s = spectrogram( x ) returns the Short-Time Fourier Transform (STFT) of the input signal x . Each column of s contains an estimate of the short-term, time-localized frequency content of x . The magnitude squared of s is known as the spectrogram time-frequency representation of x [1].