Stephen C. Ashmore

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We present a method for training a deep neural network containing sinusoidal activation functions to fit to time-series data. Weights are initialized using a fast Fourier transform, then trained with regular-ization to improve generalization. A simple dynamic parameter tuning method is employed to adjust both the learning rate and regularization term, such(More)
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