Enhanced synaptic characteristics of H x WO3-based neuromorphic devices, achieved by current pulse control, for artificial neural networks

Abstract

Artificial synapses capable of mimicking the fundamental functionalities of biological synapses are critical to the building of efficient neuromorphic systems. We have developed a H _x WO _3 -based artificial synapse that replicates such synaptic functionalities via an all-solid-state redox transistor mechanism. The subject synaptic-H _x WO _3 transistor, which operates by current pulse control, exhibits excellent synaptic properties including good linearity, low update variation and conductance modulation characteristics. We investigated the performance of the device under various operating conditions, and the impact of the characteristics of the device on artificial neural network computing. Although the subject synaptic-H _x WO _3 transistor showed an insufficient recognition accuracy of 66% for a handwritten digit recognition task with voltage pulse control, it achieved an excellent accuracy of 88% with current pulse control, which is approaching the 93% accuracy of an ideal synaptic device. This result suggests that the performance of any redox-transistor-type artificial synapse can be dramatically improved by current pulse control, which in turn paves the way for further exploration and the evolution of advanced neuromorphic systems, with the potential to revolutionize the artificial intelligence domain. It further marks a significant stride towards the realization of high-performance, low-power consumption computing devices.

Keywords

• artificial synapse
• redox-transistor
• current pulse control
• artificial neural networks
• H x WO3