Modelling of active microwave transistors using artificial neural networks

Signal and noise behaviours of microwave transistors are modeled through the neural network approach for the whole operating ranges including frequency bias and configuration types. Here, the device is modeled by a black box whose small-signal and noise parameters are evaluated through various neural network methods, based upon the fitting of both of these parameters for multiple bias and configuration. Previous results are improved with a conic section function neural network method presented in this work.