Memristive Devices: Analog–Digital Hybrid Memristive Devices for Image Pattern Recognition with Tunable Learning Accuracy and Speed (Small Methods 10/2019). Issue 10 (15th October 2019)

• Record Type: Journal Article
• Authors: Lin, Ya; Wang, Cong; Ren, Yanyun; Wang, Zhongqiang; Xu, Haiyang; Zhao, Xiaoning; Ma, Jiangang; Liu, Yichun
• Is Part Of: Small methods. Volume 3:Issue 10(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-10-15
• Subjects: analog resistive switching -- digital resistive switching -- memristors -- pattern recognition -- spike‐timing‐dependent plasticity; Nanotechnology -- Methodology -- Periodicals; Nanotechnology -- Periodicals; Periodicals; 620.5028
• DOI: 10.1002/smtd.201970031
• Languages: English
• ISSNs: 2366-9608

Abstract

Abstract : In article number1900160 by Zhongqiang Wang, Haiyang Xu and co‐workers, an Au/WO3−x /Ti memristive device is demonstrated that can exhibit hybrid analog and digital resistive switching behavior by relying on interface and bulk conductance modulation, respectively. Using a spike‐timing‐dependent plasticity learning scheme, an effective method is developed to tune learning accuracy and speed of pattern recognition by adjusting the proportion of analog to digital devices in the memristor crossbar array.