Abstract
Recent advance of artificial intelligence comes from the rapid growth of artificial neural network technology. Memristors play a crucial role in the hardware implementation of artificial neural networks, thanks to the multilevel conductance of memristors by switching behaviors. Here, we propose a synaptic device with a Pr0.7Ca0.3MnO3 (PCMO) switching layer which shows the abrupt SET and gradual RESET switching characteristics. Improved linearity of the synaptic transmission caused by switching characteristics can enhance the classification performance of neuromorphic systems.
| Original language | English |
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| Title of host publication | 8th International Winter Conference on Brain-Computer Interface, BCI 2020 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781728147079 |
| DOIs | |
| Publication status | Published - 2020 Feb |
| Event | 8th International Winter Conference on Brain-Computer Interface, BCI 2020 - Gangwon, Korea, Republic of Duration: 2020 Feb 26 → 2020 Feb 28 |
Publication series
| Name | 8th International Winter Conference on Brain-Computer Interface, BCI 2020 |
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Conference
| Conference | 8th International Winter Conference on Brain-Computer Interface, BCI 2020 |
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| Country | Korea, Republic of |
| City | Gangwon |
| Period | 20/2/26 → 20/2/28 |
Keywords
- memristor
- neural network
- neuromorphic system
- synapse
ASJC Scopus subject areas
- Behavioral Neuroscience
- Cognitive Neuroscience
- Artificial Intelligence
- Human-Computer Interaction
Cite this
Pyo, Y., Nahm, S., Jeong, J., & Shin, J. (2020). Implementation of hardware-based neural network using memristors with abrupt SET and gradual RESET characteristics. In 8th International Winter Conference on Brain-Computer Interface, BCI 2020 [9061641] (8th International Winter Conference on Brain-Computer Interface, BCI 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BCI48061.2020.9061641