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Simple Artificial Neuron Using an Ovonic Threshold Switch Featuring Spike-Frequency Adaptation and Chaotic Activity
Physical Review Applied ( IF 4.6 ) Pub Date : 2020-06-23 , DOI: 10.1103/physrevapplied.13.064056
Milim Lee , Seong Won Cho , Seon Jeong Kim , Joon Young Kwak , Hyunsu Ju , Yeonjin Yi , Byung-ki Cheong , Suyoun Lee

As an essential building block for developing a large-scale brain-inspired computing system, we propose a highly scalable and energy-efficient artificial neuron device composed of an ovonic threshold switch (OTS) and a few passive electrical components. It is found that the proposed neuron device shows not only the basic integrate-and-fire function and the rate-coding property, but also the spike-frequency-adaptation (SFA) property and the chaotic activity of biological neurons, the most common features found in mammalian cortex, but they have been hard to achieve up to now. In addition, it is shown that the energy consumption of the OTS-based neuron device scales with the size of the OTS device, extrapolating both the size and the energy efficiency to the level of a biological neuron in a human brain with state-of-the-art technology. Finally, using the OTS-based neuron device combined with the reservoir computing technique, the spoken-digit recognition task has been performed with a considerable degree of recognition accuracy (94%). These results demonstrate that our OTS-based artificial neuron device is promising for the application in the development of a large-scale brain-inspired computing system.

中文翻译:

简单的人工神经元,使用具有峰值频率适应和混沌活动的Ovonic门限开关

作为开发大规模灵感来自大脑的计算系统的基本组成部分,我们提出了一种高度可扩展且高效节能的人工神经元设备,该设备由卵形阈值开关(OTS)和一些无源电子组件组成。发现所提出的神经元装置不仅表现出基本的积分发射功能和速率编码特性,而且还表现出尖峰频率自适应(SFA)特性和生物神经元的混沌活动,这是最常见的特征。在哺乳动物皮层中发现,但至今仍难以实现。此外,还表明基于OTS的神经元设备的能量消耗随OTS设备的大小而变化,从而将大小和能量效率都推算为人脑中状态为生物神经元的水平。最先进的技术。最后,使用基于OTS的神经元设备与储层计算技术相结合,已以相当高的识别精度(94%)执行了语音识别任务。这些结果表明,我们基于OTS的人工神经元设备有望在大规模的脑启发式计算系统的开发中得到应用。
更新日期:2020-06-24
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