Neural-Based Models of Semiconductor Devices for SPICE Simulator
Abstract
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.
DOI: https://doi.org/10.3844/ajassp.2008.385.391
Copyright: © 2008 Hanene Ben Hammouda, Mongia Mhiri, Zièd Gafsi and Kamel Besbes. This is an open access article distributed under the terms of the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Artificial Neural Networks
- new semiconductor devices
- SPICE
- Modeling
- Taylor series expansion