Neural-Based Models of Semiconductor Devices for SPICE Simulator

The paper addresses a simple and fast new approach to implement Artificial Neural Networks (ANN) models for the MOS transistor into SPICE. The proposed approach involves two steps, the modeling phase of the device by NN providing its input/output patterns, and the SPICE implementation process of the resulting model. Using the Taylor series expansion, a neural based small-signal model is derived. The reliability of our approach is validated through simulations of some circuits in DC and small-signal analyses.