Programmable CNN cell based on SET transistors

This paper presents a neuron structure that resembles the basic McCulloch and Pitts model and is suitable for an implementation with single-electron tunneling (SET) transistors only or as a SET/FET hybrid. It combines a basic neuron with nine binary-programmable synapses and a programmable bias term. With these synaptic inputs the neuron is suitable for building a processing array like the cellular neural network (CNN) for processing black and white (BAY) images. The binary programming scheme is fast and robust, and thus it can be applied to architectures based on nanodevices. The cell structure and operation principles are described and illustrated by simulation results