TY - JOUR
T1 - Research progress of artificial neural systems based on memristors
AU - Tang, Zheng
AU - Sun, Bai
AU - Zhou, Guangdong
AU - Zhou, Yongzan
AU - Cao, Zelin
AU - Duan, Xuegang
AU - Yan, Wentao
AU - Chen, Xiaoliang
AU - Shao, Jinyou
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2024/3
Y1 - 2024/3
N2 - 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.
AB - 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.
KW - Artificial neural system
KW - Electronic skin
KW - Memristor
KW - Nociceptor
KW - Reflex arc
KW - Synapse
UR - https://www.scopus.com/pages/publications/85178106246
U2 - 10.1016/j.mtnano.2023.100439
DO - 10.1016/j.mtnano.2023.100439
M3 - 文献综述
AN - SCOPUS:85178106246
SN - 2588-8420
VL - 25
JO - Materials Today Nano
JF - Materials Today Nano
M1 - 100439
ER -