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ISSN: 1546-9239 (Print)
ISSN: 1554-3641 (Online)
Research Article Open Access

Neural-Based Models of Semiconductor Devices for SPICE Simulator

Hanene Ben Hammouda, Mongia Mhiri, Zièd Gafsi and Kamel Besbes

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.

American Journal of Applied Sciences
Volume 5 No. 4, 2008, 385-391

DOI: https://doi.org/10.3844/ajassp.2008.385.391

Submitted On: 26 July 2007 Published On: 30 April 2008

How to Cite: Hammouda, H. B., Mhiri, M., Gafsi, Z. & Besbes, K. (2008). Neural-Based Models of Semiconductor Devices for SPICE Simulator. American Journal of Applied Sciences, 5(4), 385-391. https://doi.org/10.3844/ajassp.2008.385.391

Open AccessCopyright: © 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