تقرير
A highly scalable and energy-efficient artificial neuron using an Ovonic Threshold Switch (OTS) featuring the spike-frequency adaptation and chaotic activity
| العنوان: | A highly scalable and energy-efficient artificial neuron using an Ovonic Threshold Switch (OTS) featuring the spike-frequency adaptation and chaotic activity |
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| المؤلفون: | Lee, Milim, Kim, Youngjo, Cho, Seong Won, Kwak, Joon Young, Ju, Hyunsu, Yi, Yeonjin, Cheong, Byung-ki, Lee, Suyoun |
| المصدر: | Phys. Rev. Applied 13, 064056 (2020) |
| سنة النشر: | 2018 |
| المجموعة: | Computer Science Condensed Matter |
| مصطلحات موضوعية: | Condensed Matter - Disordered Systems and Neural Networks, Computer Science - Emerging Technologies |
| الوصف: | As an essential building block for developing a large-scale brain-inspired computing system, we present a highly scalable and energy-efficient artificial neuron device composed of an Ovonic Threshold Switch (OTS) and a few passive electrical components. It shows not only the basic integrate-and-fire (I&F) function and the rate coding ability, but also the spike-frequency adaptation (SFA) property and the chaotic activity. The latter two, being the most common features found in the mammalian cortex, are particularly essential for the realization of the energy-efficient signal processing, learning, and adaptation to environments1-3, but have been hard to achieve up to now. Furthermore, with our OTS-based neuron device employing the reservoir computing technique combined with delayed feedback dynamics, spoken-digit recognition task has been performed with a considerable degree of recognition accuracy. From a comparison with a Mott memristor-based artificial neuron device, it is shown that the OTS-based artificial neuron is much more energy-efficient by about 100 times. These results show that our OTS-based artificial neuron device is promising for the application in the development of a large-scale brain-inspired computing system. |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1103/PhysRevApplied.13.064056 |
| URL الوصول: | http://arxiv.org/abs/1810.08381 |
| رقم الأكسشن: | edsarx.1810.08381 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1103/PhysRevApplied.13.064056 |
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