Radial basis function neural network models for power-amplifier design

Abstract

A method for learning the dynamic responses of a nonlinear power-amplifier with a radial basis function (RBF) neural network is presented. The training data of the RBF neural networks are samples of the input and output waveforms of the power-amplifier. A new training scheme employing efficient gradient-based optimization methods is developed to train the… (More)

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