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Updated: Sep 23, 2025

In Situ Transmission Electron Microscopy with Biasing and Fabrication of Asymmetric Crossbars Based on Mixed-Phased a-VOx
Published on: May 13, 2020
Novel training method for metal-oxide memristive synapse device to overcome trade-off between linearity and dynamic
Jongseon Seo1, Geonhui Han1, Daeseok Lee1
1Department of Electronic Materials Engineering, Kwangwoon University, Seoul 01897, Republic of Korea.
Abstract:
Synapse devices are essential for the hardware implementation of neuromorphic computing systems. However, it is difficult to realize ideal synapse devices because of issues such as nonlinear conductance change (linearity) and a small number of conductance states (dynamic range). In this study, the correlation between the linearity and dynamic range was investigated. Consequently, we found a trade-off relationship between the linearity and dynamic range and proposed a novel training method to overcome this trade-off.
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