지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 JOURNAL OF SEMICONDUCTOR TECHNOLOGY AND SCIENCE Journal of Semiconductor Technology and Science Vol.20 No.1
- 발행연도
- 2020.2
- 수록면
- 119 - 126 (8page)
- DOI
- 10.5573/JSTS.2020.20.1.119
이용수
초록· 키워드
오류제보하기
Recently, researchers have been paying more attention to hardware neural networks with memory devices acting as synapses due to their small area and low power consumption. We prefer to use a phase-change memory (PCM) device as a synapse due to its excellent synapse-like properties. However, due to the programming mechanism of PCMs, the asymmetric characteristic of the PCM between partially set and partially reset is severe. In this paper, we proposed an alternate pulse scheme (APS) to reduce the influence of the asymmetry between long-term potentiation and long-term depression operations.
목차
Abstract
I. INTRODUCTION
II. PCM DEVICE AS SYNAPSE
III. NEURAL NETWORK
IV. PROPOSED ALTERNATE PULSE SCHEME
V. CONCLUSIONS AND DISCUSSION
REFERENCES
참고문헌 (20)
참고문헌 신청
D. Kuzum, et al, “Nanoelectronic programmable synapses based on phase change materials for brain-inspired computing,” Nano letters, Vol. 12, No. 5, pp. 2179-2186, 2011.
M. J. Breitwisch, R. W. Cheek, C. H. Lam, D. S. Modha, B. Rajendran,: US Patent 20100299297.
S. Kim, et al, “NVM neuromorphic core with 64kcell (256-by-256) phase change memory synaptic array with on-chip neuron circuits for continuous in-situ learning,” 2015 IEEE international electron devices meeting (IEDM), pp. 17.1.1-17.1.4., 2015.
Z. Wang, et al, “A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systems,” Frontiers in neuroscience, vol. 8, pp. 438, 2015.
A. Pantazi, et al, “All-memristive neuromorphic computing with level-tuned neurons,” Nanotechnology, Vol. 27, No. 35, pp. 355205, 2016.
M. J. Breitwisch, R. W. Cheek, C. H. Lam, D. S. Modha, B. Rajendran,: US Patent 20100299297.
S. Kim, et al, “NVM neuromorphic core with 64kcell (256-by-256) phase change memory synaptic array with on-chip neuron circuits for continuous in-situ learning,” 2015 IEEE international electron devices meeting (IEDM), pp. 17.1.1-17.1.4., 2015.
Z. Wang, et al, “A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systems,” Frontiers in neuroscience, vol. 8, pp. 438, 2015.
A. Pantazi, et al, “All-memristive neuromorphic computing with level-tuned neurons,” Nanotechnology, Vol. 27, No. 35, pp. 355205, 2016.
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