Artificial neural network based modeling of FinFET forward transmission coefficient

This paper gives a comprehensive analysis of modeling of the FinFET forward transmission coefficient by using artificial neural networks. Models for the whole device and the actual device obtained after applying the de-embedding procedure the effects of pads, transmission lines, and substrate have been developed and validated in a wide range of bias conditions for frequencies up to 50 GHz. Special attention has been paid to the modeling of kink effects at low frequencies caused by lossy silicon substrate.