The S-transform with windows of arbitrary and varying shape

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A basis for efficient representation of the S-transform (2007, background): “The utility of S-transform analysis of a time series has been demonstrated in a range of geophysical fields such as: (i) analyzing internal atmospheric wave packets [20,21], (ii) atmospheric studies [22–26], (iii) characterization of seismic signals [27–30], (iv) global sea surface temperature analy”
Time-frequency feature representation using energy concentration: An overview of recent advances (2009, methodology): “This generalization also allows nonsymmetric windows to be used [47], [48].”
Detection and Classification of Power Quality Disturbances Using S-Transform and Probabilistic Neural Network (2008, background): “The choice of windowing function is not limited to the Gaussian function, other windowing functions were also implemented successfully [13].”
Letter to the Editor: Stockwell and Wavelet Transforms (2006, background): “One notes, for instance, the work of Pinnegar [ 38 ] on generalized Stockwell transforms, which introduces adjustable windows for improved time or frequency resolution.”