Comparison of volterra models extracted from a Neural Network for nonlinear systems modeling

Abstract

In this paper, a Time-Delayed feed-forward Neural Network (NN) is used to make an input-output time-domain characterization of a nonlinear electronic device. The procedure provides also an analytical expression for its behavior, the Volterra Series model, to predict the device response to multiple input power levels. This model, however, can be built to different accuracy degrees, depending on the activation function chosen for the NN used. We compare two Volterra series models extracted from different networks, having hyperbolic tangent and polynomial activation functions. This analysis is applied to the modeling of a Power Amplifier (PA). © Springer-Verlag Berlin Heidelberg 2005.