记忆电阻器
人工神经网络
计算机科学
人工智能
过程(计算)
神经系统
工程类
控制工程
电子工程
神经科学
生物
操作系统
作者
Zheng Tang,Bai Sun,Guangdong Zhou,Yongzan Zhou,Zelin Cao,Xuegang Duan,Wentao Yan,Xiaoliang Chen,Jinyou Shao
标识
DOI:10.1016/j.mtnano.2023.100439
摘要
The artificial nervous system includes electronic devices designed to simulate the functions of the biological nervous system, thereby endowing them with the ability to perceive, storage, process, and respond to external stimuli. It is worth noting that artificial neural systems based on memristors have attracted great attention in recent years, mainly due to the inherent characteristics of memristors, such as their adaptive resistance characteristics similar to bio-synapse, low power consumption, high operating speed, and seamless integration ability. This paper reviews the research progress of memristor-based artificial neural systems in reflex arc, electronic skin (e-skin), nociceptor, and computing. Then it introduces the different types of mainstream resistance switching mechanisms of memristors. Furthermore, this paper looks into the future and considers potential avenues for the application of artificial neural systems based on memristors in intelligent devices and robots. By elucidating the development and current state of artificial neural systems based on memristors, it is hoped that researchers can better understand their characteristics and potential applications. Therefore, this review not only provides a detailed discussion of the research progress, but also highlights the interesting challenges faced in leveraging these systems to create intelligent technologies.
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