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This paper describes an application of the structured genetic algorithm to the construction of microwave circuit neural network models. The algorithm is used to create a neural network model of a high electron mobility transistor (HEMT) power amplifier. Results are compared to other neural network training algorithms such as back-propagation and the Levenberg-Marquardt algorithm. Models of one and two-stage amplifiers created with the ADS circuit simulator give good predictions of measurement results.