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논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2020.8
- 수록면
- 163 - 166 (4page)
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초록· 키워드
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In this paper, we investigate the hardware-based off-chip learning spiking neural network (SNN) system using gated Schottky diode (GSD) as a synaptic device and integrate and fire neuron circuit (I&F circuit). Through Xmodel simulation, we evaluate the inference accuracy of a 2-layer neural network for MNIST pattern recognition. The classification accuracy rate of 100 images from MNIST test sets is 94%. This result means that the system works well, and the accuracy is comparable to the reference accuracy obtained with software. Furthermore, the relationship between threshold voltage and membrane capacitance of integrate and fire neuron is analyzed.
목차
Abstract
Ⅰ. Introduction
Ⅱ. Building blocks of SNN system
Ⅲ. Hardware-Based SNN
Ⅳ. Results and Discussion
Ⅴ. Conclusion
References
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UCI(KEPA) : I410-ECN-0101-2020-569-001128149