神经形态工程学
计算机科学
冯·诺依曼建筑
记忆电阻器
人工神经网络
人工智能
信号处理
计算机体系结构
工程类
计算机硬件
电子工程
数字信号处理
操作系统
作者
Qifeng Lu,Yinchao Zhao,Long Huang,Jiabao An,Yufan Zheng,Eng Hwa Yap
出处
期刊:Nanomaterials
[MDPI AG]
日期:2023-01-17
卷期号:13 (3): 373-373
被引量:8
摘要
With the rapid development of artificial intelligence and the Internet of Things, there is an explosion of available data for processing and analysis in any domain. However, signal processing efficiency is limited by the Von Neumann structure for the conventional computing system. Therefore, the design and construction of artificial synapse, which is the basic unit for the hardware-based neural network, by mimicking the structure and working mechanisms of biological synapses, have attracted a great amount of attention to overcome this limitation. In addition, a revolution in healthcare monitoring, neuro-prosthetics, and human-machine interfaces can be further realized with a flexible device integrating sensing, memory, and processing functions by emulating the bionic sensory and perceptual functions of neural systems. Until now, flexible artificial synapses and related neuromorphic systems, which are capable of responding to external environmental stimuli and processing signals efficiently, have been extensively studied from material-selection, structure-design, and system-integration perspectives. Moreover, low-dimensional materials, which show distinct electrical properties and excellent mechanical properties, have been extensively employed in the fabrication of flexible electronics. In this review, recent progress in flexible artificial synapses and neuromorphic systems based on low-dimensional materials is discussed. The potential and the challenges of the devices and systems in the application of neuromorphic computing and sensory systems are also explored.
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