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We propose to use the Generalized Morse Wavelets (GMWs) instead ofcommonly-used Morlet (or Gabor) wavelets in the Scattering Transform Network(STN), which we call the GMW-STN, for signal classification problems. The GMWsform a parameterized family of truly analytic wavelets while the Morletwavelets are only approximately analytic. The analyticity of underlying waveletfilters in the STN is particularly important for nonstationary oscillatorysignals such as music signals because it improves interpretability of the STNrepresentations by providing multiscale amplitude and phase (and consequentlyfrequency) information of input signals. We demonstrate the superiority of theGMW-STN over the conventional STN in music genre classification using theso-called GTZAN database. Moreover, we show the performance improvement of theGMW-STN by increasing its number of layers to three over the typical two-layerSTN.}

The Scattering Transform Network with Generalized Morse Wavelets and Its Application to Music Genre Classification