Accurate and efficient small-signal modeling of active devices using artificial neural networks

Abstract

Artificial neural networks (ANNs) are presented for the accurate and efficient small-signal modeling of active devices. Models are developed using measured data and are valid over ranges of parameters such as frequency, bias, and ambient temperature. Once generated, these ANN models are inserted into commercial microwave circuit simulators where they can be used for computer-aided design (CAD) and optimization of microwave/MM-wave circuits. Also, the developed ANN models can give physical insight into device behavior and scaling properties when used in conjunction with an equivalent circuit approach. An advantage of the ANN modeling approach is that it provides substantial data storage reduction over previously used modeling techniques without loss of accuracy. With increased model accuracy, the potential of first-pass design success may be realized, resulting in cost savings and decreased time-to-market for new products.