Affiliation:
1. School of Microelectronics Fudan University Shanghai 200433 China
2. National Integrated Circuit Innovation Center No.825 Zhangheng Road Shanghai 201203 China
Abstract
AbstractWith the rapid development of artificial intelligence (AI), there is an urgent need for developing a biological sensory perception system that can simulate the human brain for information processing. Inspired by the biological vision system, photo‐responsive photonic synapses are ideal devices for constructing photosensitive artificial neural networks for neuromorphic computing tasks. This paper reports a stable photonic synaptic device in an array layout with adjustable synaptic plasticity under ultraviolet light pulses. Since the heterojunction has a photoconductivity effect and the trap layer provides superior charge carrier trapping capability, optical sensing, memory, and neuromorphic computing are integrated into a single device. Meanwhile, supervised learning of handwritten digitals is achieved by exploiting the multistate conductance by photoelectric co‐modulation and the specific decay law. The recognition rate reaches 90.6% and hardly changes with time. Additionally, the device can simplify the artificial neural network (ANN) and reduce its size to 3.78% of the original network while retaining strong fault tolerance and learning ability. The photonic artificial synapses based on ultraviolet light modulation provide a novel and effective approach for photosensory ANNs to perform in situ computation.
Funder
Science and Technology Commission of Shanghai Municipality
China Postdoctoral Science Foundation
Subject
Electronic, Optical and Magnetic Materials
Cited by
1 articles.
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