Spectrogram Producing Algorithms

• represents a signal in the time-frequency domain by computing discrete Fourier transforms (DFT) over short overlapping windows
• it is used to compute a spectrogram

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• is a special case of the short-time Fourier transform where the window function is a Gaussian function
• the problem Gabor transforms tries to solve is that the Fourier transform takes pure time/spatial data and transforms it into pure frequency data. There’s nowhere in between to look at data in both the time and frequency domain, which is what Gabor Transforms is used for.
• it is used to compute the spectrogram
• it is used to determine the sinusoidal frequency and phase content of local sections of a signal as it changes over time

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• generalizes the Fourier transform and is better suited to multi-scale data
• it is like the Gabor Transform but takes advantage of the idea that lower frequencies tend to last for a long time, and higher frequencies tend to change faster in time

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