The sliding Fourier transform is widely used for extracting time-dependent spectra from time series and has localization properties similar to those of the wavelet transformations. It is described here to provide a contrast to the wavelet transforms. To create a sliding Fourier transform, a time series is cut into a series of smaller series, which are then individually Fourier transformed. This windowing creates a transformation that is localized in time.
发表于 2007-1-27 20:40
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