Neuromorphic Devices, Circuits, and Their Applications in Flexible Electronics

被引:3
|
作者
Wang, Feiyu [1 ]
Zhang, Tongju [1 ]
Dou, Chunmeng [2 ]
Shi, Yi [1 ]
Pan, Lijia [1 ]
机构
[1] Nanjing University, Collaborative Innovation Center of Advanced Microstructures, School of Electronic Science and Engineering, Nanjing,210093, China
[2] Institute of Microelectronics, Chinese Academy of Sciences, Key Laboratory of Microelectronics Devices and Integrated Technology, Beijing,100029, China
来源
关键词
Computer architecture - Flexible electronics - Neural networks - Wearable technology;
D O I
10.1109/JFLEX.2023.3321256
中图分类号
学科分类号
摘要
Artificial intelligence (AI) has rapidly evolved and sparked a heightened interest in the field of bionic electronics. A key focus in this field is to emulate biological neural networks and create perceptually sensitive and adaptable neuromorphic devices. These devices are essential components for the next-generation flexible wearables, smart textiles, biomedical devices, and soft robots. The remarkable advantage of flexible neuromorphic devices lies in their ability to directly perceive, store, and analyze diverse information from the external environment. A notable feature is the integration of multisensory inputs in flexible neuromorphic devices, which enables enhanced adaptability to complex and dynamic scenarios that may occur in reality. This comprehensive review examines the structure and functionality of biological synapses and the prospective designs of neuromorphic devices that emulate synaptic functions. We review recent advances in neuromorphic devices and flexible electronic circuits, including different types of neuromorphic devices, such as two-terminal memristors and three-terminal synaptic transistors. We also compare their advantages and limitations. Finally, we discuss the challenges and opportunities for the future development of flexible neuromorphic devices. This review reveals the great potential of neuromorphic devices, circuits, and their applications in flexible electronics and provides valuable insights into the current state-of-the-art and prospects of this field. © 2022 IEEE.
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页码:42 / 56
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