A VOx based optoelectronic memristor for application in visual perception

Abstract

Abstract While biological vision systems excel at in-memory processing with low power consumption, traditional silicon-based vision chips struggle with high energy demands. This gap motivates the exploration of alternative materials for artificial intelligence applications. This paper presents a VOx-based optoelectronic synaptic memristive device. The proposed artificial synaptic device ITO/VOx /Pt mimics biological functions such as potentiation (P), depression (D), long-term memory (LTM), short-term memory (STM), and paired-pulse facilitation (PPF). The PPF index, standing at 105%, suggests a favorable pattern in short-term memory function. The device served as synapses within a spiking neural network (SNN) showing an achievable pattern classification accuracy of 88.68%, highlighting the potential of the VOx synaptic device for pattern classification tasks. The proposed VOx-based synaptic devices could be a promising platform for efficient pattern recognition and visual perception applications.