(Journal of Computer Science y Technology., 2019) García, Mario Alejandro; Destefanis , Eduardo
A model of neural network with convolutional layers
that calculates the power cepstrum of the input signal
is proposed. To achieve it, the network calculates the
discrete-time short-term Fourier transform internally,
obtaining the spectrogram of the signal as an interme diate step. Although the proposed neural networks
weights can be calculated in a direct way, it is nec essary to determine if they can be obtained through
training with the gradient descent method. In order to
analyse the training behaviour, tests are made on the
proposed model, as well as on two variants (power
spectrum and autocovariance). Results show that the
calculation model of power cepstrum cannot be trained,
but the analysed variants in fact can.
