Advanced synaptic devices and their applications in biomimetic sensory neural system
Yiqi Sun,
Jiean Li,
Sheng Li,
Yongchang Jiang,
Enze Wan,
Jiahan Zhang,
Yi Shi,
Lijia Pan
Affiliations
Yiqi Sun
School of Electronic Science and Engineering, Nanjing University, 210093, Nanjing, China
Jiean Li
School of Electronic Science and Engineering, Nanjing University, 210093, Nanjing, China
Sheng Li
School of Electronic Science and Engineering, Nanjing University, 210093, Nanjing, China; School of Microelectronics and Control Engineering, Changzhou University, 213164, Changzhou, China; Corresponding authors.
Yongchang Jiang
School of Electronic Science and Engineering, Nanjing University, 210093, Nanjing, China
Enze Wan
School of Computer Science and Engineering, Macau University of Science and Technology
Jiahan Zhang
School of Electronic Science and Engineering, Nanjing University, 210093, Nanjing, China
Yi Shi
School of Electronic Science and Engineering, Nanjing University, 210093, Nanjing, China
Lijia Pan
School of Electronic Science and Engineering, Nanjing University, 210093, Nanjing, China; Corresponding authors.
ABSTRACT: Human nervous system, which is composed of neuron and synapse networks, is capable of processing information in a plastic, data-parallel, fault-tolerant, and energy-efficient approach. Inspired by the ingenious working mechanism of this miraculous biological data processing system, scientists have been devoting great efforts to artificial neural systems based on synaptic devices in recent decades. The continuous development of bioinspired sensors and synaptic devices in recent years have made it possible that artificial sensory neural systems are capable of capturing and processing stimuli information in real time. The progress of biomimetic sensory neural systems could provide new methods for next-generation humanoid robotics, human-machine interfaces, and other frontier applications. Herein, this review summarized the recent progress of synaptic devices and biomimetic sensory neural systems. Additionally, the opportunities and remaining challenges in the further development of biomimetic sensory neural systems were also outlined.
