STFT with varying window lengths (like the continuous wavelet transform)

1. What is the difference between STFT and wavelet transform?
2. What is the main advantage of wavelet analysis over STFT?
3. What does a continuous wavelet transform do?
4. How does window length affect 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.

What is the main advantage of wavelet analysis over STFT?

Wavelet analysis overcomes the disadvantage of STFT since CWT uses a windowing technique with variable sized regions. Wavelet analysis allows the use of long time intervals where we want more precise low-frequency information, and shorter regions where we want high-frequency information.

What does a continuous wavelet transform do?

In mathematics, the continuous wavelet transform (CWT) is a formal (i.e., non-numerical) tool that provides an overcomplete representation of a signal by letting the translation and scale parameter of the wavelets vary continuously.

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.