Time-frequency analysis: theory and applications
Time-frequency analysis: theory and applications
SIAM Journal on Scientific Computing
Localization of the complex spectrum: the S transform
IEEE Transactions on Signal Processing
A new subclass of complex-valued S-transform windows
Signal Processing - Special section: Advances in signal processing-assisted cross-layer designs
A basis for efficient representation of the S-transform
Digital Signal Processing
A window width optimized S-transform
EURASIP Journal on Advances in Signal Processing
Time--frequency feature representation using energy concentration: An overview of recent advances
Digital Signal Processing
Statistical denoising of signals in the S-transform domain
Computers & Geosciences
Time--frequency and time--time filtering with the S-transform and TT-transform
Digital Signal Processing
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The S-transform was originally defined as a method of determining the local spectrum of a time series, through the use of a translating, real Gaussian window that dilates to accomodate the different cycle durations of different frequencies. The S-transform "wavelet" is obtained by multiplying this real window with the complex Fourier sinusoid. Since the Fourier sinusoid has time-invariant frequency, the S-transform is consequently unsuitable for resolving waveforms whose frequency changes with time. This problem can be addressed by introducing a complex Gaussian window, with a user designed, complex phase function. The phase function modulates the frequency of the Fourier sinusoid to give a specific waveform, leading to better time frequency localization of similar waveforms on the time series. The complex-window S-transform is similar to a wavelet transform, but has the fixed phase reference of the Fourier transform.