Howtosignalprocessing
- Why is wavelet transform better than Fourier transforms?
- What are the advantages of short time Fourier transformation over Fourier transform?
- What is the main advantage of wavelet analysis over STFT?
- What is the difference between STFT and wavelet transform?
Why is wavelet transform better than Fourier transforms?
While the Fourier transform creates a representation of the signal in the frequency domain, the wavelet transform creates a representation of the signal in both the time and frequency domain, thereby allowing efficient access of localized information about the signal.
What are the advantages of short time Fourier transformation over Fourier transform?
STFT provides the time-localized frequency information for situations in which frequency components of a signal vary over time, whereas the standard Fourier transform provides the frequency information averaged over the entire signal time interval.
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 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.
