VO2 Carbon Nanotube Composite Memristor-Based Cellular Neural Network Pattern Formation

Yiran Shen,Guangyi Wang

doi:10.3390/electronics10101198

Abstract

A cellular neural network (CNN) based on a VO2 carbon nanotube memristor is proposed in this paper. The device is modeled by SPICE at first, and then the cell dynamic characteristics based on the device are analyzed. It is pointed out that only when the cell is at the sharp edge of chaos can the cell be successfully awakened after the CNN is formed. In this paper, we give the example of a 5 × 5 CNN, set specific initial conditions and observe the formed pattern. Because the generated patterns are affected by the initial conditions, the cell power supply can be pre-programmed to obtain specific patterns, which can be applied to the future information processing system based on complex space–time patterns, especially in the field of computer vision.

Highlights

The traditional processor uses the von Neumann structure, in which the storage unit and the processing unit are separated and connected by bus
For devices with a critical size between 50 and 600 nm, the change coefficient of the switch threshold voltage is less than 13%, the switch durability is more than 26.6 million cycles, and the IV characteristics of the device are not changed
Electronics 2021, 10, 1198 change coefficient of the switch threshold voltage is less than 13%, the switch durability is more than 26.6 million cycles, and the IV characteristics of the device are not changed significantly

Summary

Introduction

The traditional processor uses the von Neumann structure, in which the storage unit and the processing unit are separated and connected by bus. The VO2 carbon nanotube (CNT) composite device is a Mott memristor recently proposed [16]. It can generate periodic peak pulses with a pulse width of less than 20 ns, it is driven by a DC current or voltage, and it does not need additional capacitance. Non-electric formation ates the development of an technology active memristor neuron. It can simulateaccelerates the most the development of an active neuron circuit. The VO2 memristor is superior to its NbO2 counterpart in both switch switch speed and switching energy. Part of this paper is the modeling of VO2 CNT composite devices, providing the SPICE. Can largely save power and chip area, and provide ultra-high processing speeds

VO22 Carbon

Quasi-static volt-ampere characteristics of the VOVO

Cell Circuit

CNN and Simulation

Findings

5.5.Conclusions