Implementation of hardware-based neural network using memristors with abrupt SET and gradual RESET characteristics

Yeon Pyo; Sahn Nahm; Jichai Jeong; Jaeyoung Shin

doi:10.1109/BCI48061.2020.9061641

Implementation of hardware-based neural network using memristors with abrupt SET and gradual RESET characteristics

Yeon Pyo, Sahn Nahm, Jichai Jeong, Jaeyoung Shin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

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
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	https://doi.org/10.1109/BCI48061.2020.9061641
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

Conference

Conference	8th International Winter Conference on Brain-Computer Interface, BCI 2020
Country/Territory	Korea, Republic of
City	Gangwon
Period	20/2/26 → 20/2/28

Bibliographical note

Funding Information:
This work was supported in part by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government(MSIT) (No. 2017-0-00451) and the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology under Grant NRF-2018R1D1A1B07042378.

Publisher Copyright:
© 2020 IEEE.

Keywords

memristor
neural network
neuromorphic system
synapse

ASJC Scopus subject areas

Behavioral Neuroscience
Cognitive Neuroscience
Artificial Intelligence
Human-Computer Interaction

Access to Document

10.1109/BCI48061.2020.9061641

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 Article 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

Implementation of hardware-based neural network using memristors with abrupt SET and gradual RESET characteristics. / Pyo, Yeon; Nahm, Sahn; Jeong, Jichai et al.
8th International Winter Conference on Brain-Computer Interface, BCI 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9061641 (8th International Winter Conference on Brain-Computer Interface, BCI 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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., 8th International Winter Conference on Brain-Computer Interface, BCI 2020, Gangwon, Korea, Republic of, 20/2/26. https://doi.org/10.1109/BCI48061.2020.9061641

Pyo Y, Nahm S, Jeong J, Shin J. 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. Institute of Electrical and Electronics Engineers Inc. 2020. 9061641. (8th International Winter Conference on Brain-Computer Interface, BCI 2020). doi: 10.1109/BCI48061.2020.9061641

Pyo, Yeon ; Nahm, Sahn ; Jeong, Jichai et al. / Implementation of hardware-based neural network using memristors with abrupt SET and gradual RESET characteristics. 8th International Winter Conference on Brain-Computer Interface, BCI 2020. Institute of Electrical and Electronics Engineers Inc., 2020. (8th International Winter Conference on Brain-Computer Interface, BCI 2020).

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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.",

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Implementation of hardware-based neural network using memristors with abrupt SET and gradual RESET characteristics

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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