Artificial Neural Networks for RF Component Modeling

In the past two decades, artificial neural networks have been recognized as an efficient alternative for modeling microwave active and passive components. The neural network model can accurately represent measured behavior with less fitting effort, compared to conventional empirical models. However, it also faces challenges when the model is used outside of training range. This talk will be focused on using artificial neural networks for modeling RFIC passive components and RF power transistors.