Essential Characteristics of Memristors for Neuromorphic Computing (Adv. Electron. Mater. 2/2023). (10th February 2023)

• Record Type: Journal Article
• Authors: Chen, Wenbin; Song, Lekai; Wang, Shengbo; Zhang, Zhiyuan; Wang, Guanyu; Hu, Guohua; Gao, Shuo
• Is Part Of: Advanced Electronic Materials. Volume 9:Number 2(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-02-10
• Subjects: memristors -- neural networks -- neuromorphic computing -- reliability -- variability; Materials -- Electric properties -- Periodicals; Materials science -- Periodicals; Magnetic materials -- Periodicals; Electronic apparatus and appliances -- Periodicals; 537
• DOI: 10.1002/aelm.202370012
• Languages: English
• ISSNs: 2199-160X

Abstract

Abstract : Memristors Memristive neuromorphic computing promotes the development of humanoid robotics, and its performance is directly affected by the memristors' characteristics. In article number 2200833, Wenbin Chen, Shuo Gao, and co‐workers overview the recent progress of memristors with different physical mechanisms and their characteristics. The existing issues and challenges in implementing neuromorphic computing systems based on these different mechanisms are highlighted and prospected.