Two-Terminal Photoelectric Dual Modulation Synaptic Devices for Face Recognition

Neuromorphic computing systems based on artificial synapses have showed considerable potential in the field of brain-like research. Herein, a two-terminal artificial synaptic device with photoelectric dual modulation was proposed, which has the advantages of simple fabrication process and high integration density. Under photoelectric stimulation, the device could imitate the functions of synapses in the human brain, such as long-term potentiation (LTP), long-term depression (LTD), excitatory post-synaptic current (EPSC), and paired-pulse facilitation (PPF). Moreover, the device demonstrated memory capacity when triggered by several successive light pulses. The synaptic devices could be trained as neurons in artificial neural networks, and the conductance of devices could be regarded as weight of neurons. Face recognition was realized based on the synaptic weight of electrical excitation, and the recognition rate was up to 95%. This research provides a new and effective way for neuromorphic computing and image recognition with photosensitive artificial synaptic devices.