An Ultra-Low Power Threshold Voltage Variable Artificial Retina Neuron

Qiguang Wang,Guangchen Pan,Yanfeng Jiang

doi:10.3390/electronics11030365

Abstract

An artificial retina neuron is proposed and implemented by CMOS technology. It can be used as an image sensor in the Artificial Intelligence (AI) field with the benefit of ultra-low power consumption. The artificial neuron can generate signals in spike shape with pre-designed frequencies under different light intensities. The power consumption is reduced by removing the film capacitor. The comparator is adopted to improve the stability of the circuit, and the power consumption of the comparator is optimized. The power consumption of the proposed CMOS neuron circuit is suppressed. The ultra-low-power artificial neuron with variable threshold shows a frequency range of 0.8–80 kHz when the input current is varied from 1 pA to 150 pA. The minimum DC power is 35 pW when the input current is 5 pA. The minimum energy of the neuron is 3 fJ. The proposed ultra-low-power artificial retina neuron has wide potential applications in the field of AI.

Highlights

Compared with the traditional Von Neumann architecture computer, the human brain shows stronger associative memory and thinking in images
The realization of the artificial neural network (ANN) to mimic the human brain intelligence has become a hot subject for research recently [2]
The artificial neuron circuit can generate the spikes with the frequency ranging from 0.8–80 kHz when the input current is changed from 1 pA to 150 pA

Summary

Introduction

Compared with the traditional Von Neumann architecture computer, the human brain shows stronger associative memory and thinking in images. It can be seen that the function of the first-generation ANN is very limited and that it can only process binary data This is still far removed from the real biological neuron. The second-generation ANN is powerful, its energy consumption and efficiency are still not good enough compared with the biological network. There is a big difference in the process of communicating with the spikes of neurons in the human brain in the underlying logic Faced with these problems, the third-generation ANN has been proposed recently. The artificial neuron model is designed based on CMOS technology, which is used to convert the optical pixel signals into specific spikes with certain frequencies. The analysis and the results of the artificial neuron retina are reported

The Principle of Axon-Hillock Circuit

Design of Novel Artificial Neuron

Findings

Conclusions