Artificial neural network design for compact modeling of generic transistors


DOI: 10.1007/s10825-017-0984-9

Cite this article as:
Zhang, L. & Chan, M. J Comput Electron (2017). doi:10.1007/s10825-017-0984-9


A methodology to develop artificial neural network (ANN) models to quickly incorporate the characteristics of emerging devices for circuit simulation is described in this work. To improve the model accuracy, a current and voltage data preprocessing scheme is proposed to derive a minimum dataset to train the ANN model with sufficient accuracy. To select a proper network size, four guidelines are developed from the principles of two-layer network. With that, a reference ANN size is proposed as a generic three-terminal transistor model. The ANN model formulated using the proposed approach has been verified by physical device data. Both the device and circuit-level tests show that the ANN model can reproduce and predict various device and circuits with high accuracy.


Compact model Emerging device Device modeling Artificial neural network (ANN) 

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Department of ECEHong Kong University of Science and TechnologyKowloonHong Kong

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