Implementation and application of cellular neural networks based on single electron device

Abstract

This paper realizes cellular neural networks using the characteristic of negative differential resistance of hybrid single electron transistor and complementary metallic oxide semiconductor field effect transistor structure. The main building blocks consisting of cell core circuit, A and B template circuits are designed. Then a cellular neural network (CNN) is built and its application in image processing is studied. The computer simulation shows that the designed circuits are suitable for CNN implementation owing to its simple structure, low power dissipation and fast response. It could be used to form CNN of various scales so as to further increase the density of integrated circuits.