Back to Search Start Over

Optoelectronic neuron based on transistor combined with volatile threshold switching memristors for neuromorphic computing.

Authors :
Sun, Yanmei
Meng, Xinru
Qin, Gexun
Source :
Journal of Colloid & Interface Science. Jan2025:Part B, Vol. 678, p325-335. 11p.
Publication Year :
2025

Abstract

[Display omitted] • An optoelectronic spiking neuron is developed. • The gate-modulated PDVT-10 channel was combined with a volatile threshold switching memristor. • The device achieves optoelectronic performance through resistance-matching mechanism. • The neuron alters its spiking behavior in a manner resembling that of a retina. • The artificial neuron accurately replicates neuronal signal transmission in a biologically manner. The human perception and learning heavily rely on the visual system, where the retina plays a vital role in preprocessing visual information. Developing neuromorphic vision hardware is based on imitating the neurobiological functions of the retina. In this work, an optoelectronic neuron is developed by combining a gate-modulated PDVT-10 channel with a volatile threshold switching memristor, enabling the achievement of optoelectronic performance through a resistance-matching mechanism. The optoelectronic spiking neuron exhibits the ability to alter its spiking behavior in a manner resembling that of a retina. Incorporating electrical and optical modulation, the artificial neuron accurately replicates neuronal signal transmission in a biologically manner. Moreover, it demonstrates inhibition of neuronal firing during darkness and activation upon exposure to light. Finally, the evaluation of a perceptron spiking neural network utilizing these leaky integrate-and-fire neurons is conducted through simulation to assess its capability in classifying image recognition algorithms. This research offers a hopeful direction for the development of easily expandable and hierarchically structured spiking electronics, broadening the range of potential applications in biomimetic vision within the emerging field of neuromorphic hardware. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00219797
Volume :
678
Database :
Academic Search Index
Journal :
Journal of Colloid & Interface Science
Publication Type :
Academic Journal
Accession number :
180391111
Full Text :
https://doi.org/10.1016/j.jcis.2024.09.030