Electrical simulation of learning stage in OG-CNTFET based neural crossbar

As the fabrication cost of CMOS mask increases exponentially while the technology is approaching its physical limits, research interest focuses on emerging technologies and alternative architectures. Non-volatile components are considered as possible alternative technologies and neural networks constitute an interesting framework. Here, we present a learning strategy applied to a new non volatile device: the Optically Gated Carbon Nanotube Field Effect Transistor (OG-CNTFET). In this paper, electrical simulations using accurate compact model demonstrate the efficiency of this method to learn linearly separable Boolean functions.