An Introduced Intelligent Algorithm for Modelling of Microwave Transistor

neural network algorithms have been applied to a variety of areas of engineering and microwave structures. Neural networks are also able to model nonlinear relations between different data sets. Owing to this feature, an introduced neural network model (INN) based on particle swarm optimization (PSO) training algorithm (INN-PSO) is presented for pseudomorphic high electron mobility transistor (pHEMT). This global optimization algorithm is applied to avoid the local minima problem in the gradient descenttraining algorithm and to achieve acceptable solution. The proposed (INN-PSO) model is used to predict the scattering parameters for various bias values different from the ones in the data set used for training. This model has been verified by comparing predicted and measured values of a pHEMT for a certain data set of S-parameters at different frequencies and bias points. Keywords—pHEMT, S-parameters, small signal model, neural networks, particle swarm optimization.