Emerging memristors and applications in reservoir computing
作者机构：School of Physics and Optoelectronic EngineeringGuangdong University of TechnologyGuangzhou Higher Education Mega CenterGuangzhou 510006China
出 版 物：《Frontiers of physics》 (物理学前沿（英文版）)
年 卷 期：2024年第19卷第1期
页 面：219-239页
核心收录：
学科分类：08[工学] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术（可授工学、理学学位）] 0702[理学-物理学]
基 金：supported by the National Natural Science Foundation of China(Grant Nos.11574057 and 12172093) the Guangdong Basic and Applied Basic Research Foundation(Grant No.2021A1515012607).
主 题：reservoir computing memristor resistive switching artificial synapse neuromorphic computing
摘 要：Recently, with the emergence of ChatGPT, the field of artificial intelligence has garnered widespread attention from various sectors of society. Reservoir Computing (RC) is a neuromorphic computing algorithm used to analyze time-series data. Unlike traditional artificial neural networks that require the weight values of all nodes in the trained network, RC only needs to train the readout layer. This makes the training process faster and more efficient, and it has been used in various applications, including speech recognition, image classification, and control systems. Its flexibility and efficiency make it a popular choice for processing large amounts of complex data. A recent research trend is to develop physical RC, which utilizes the nonlinear dynamic and short-term memory properties of physical systems (photonic modules, spintronic devices, memristors, etc.) to construct a fixed random neural network structure for processing input data to reduce computing time and energy. In this paper, we introduced the recent development of memristors and demonstrated the remarkable data processing capability of RC systems based on memristors. Not only do they possess excellent data processing ability comparable to digital RC systems, but they also have lower energy consumption and greater robustness. Finally, we discussed the development prospects and challenges faced by memristors-based RC systems.
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