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Windowing transformations are techniques used to apply a window function to a signal or dataset to manage edge effects and improve analysis, particularly in time-frequency signal processing. These transformations help in reducing spectral leakage by multiplying the signal with a window function, which tapers the edges of the data to zero, thus ensuring a smoother transition and more accurate frequency representation.
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