Small-signal and large-signal modeling of active devices using CAD-optimized neural networks

Abstract

Artificial neural networks (ANNs) are presented for the technology-independent modeling of active devices in MMICs. ANNs trained with S-parameter and DC measurements over the entire bias and frequency operational band are used for the small-signal bias-dependent modeling of a low-noise GaAs HEMT device, without the need of the equivalent circuit parameter extraction. ANNs are also used within the large-signal model of a power MESFET device, modeling the drain-source current Ids and charges Qg and Qd obtained from integration of their partial derivatives. After training and testing, the ANN models have been implemented as two-port networks into a microwave circuit simulator. This enabled the ANN models to be used in the design, analysis, and optimization of microwave/mm-wave circuits. Improved techniques in network building to provide not only accurate but also fast simulation models have been applied. © 2002 John Wiley & Sons, Inc. Int J RF and Microwave CAE 12: 71–78, 2002.