CMOS芯片
人工神经元
人工神经网络
阈值电压
缩放比例
计算机科学
尖峰神经网络
能量(信号处理)
能源消耗
超大规模集成
逻辑门
数学
电压
算法
电气工程
电子工程
拓扑(电路)
物理
人工智能
晶体管
工程类
量子力学
几何学
作者
Yingxin Chen,Kai Xiao,Yajie Qin,Fanyu Liu,Jing Wan
标识
DOI:10.1109/led.2022.3219465
摘要
In this article, we first utilize a zero subthreshold swing and zero impact ionization FET (Z2-FET) as an innovative artificial spiking neuron and demonstrate it with CMOS-compatible technology. Owing to the sharp-switching and hysteresis characteristics of Z2-FET, the artificial neuron successfully emulates the key biological neuronal behaviors based on a single device, including threshold-driven spiking and stimulus strength-modulated frequency response. Furthermore, the firing threshold of the neuron is conveniently tuned by the gate voltage, which is helpful in the application of spiking neural networks (SNN). A preliminary endurance up to ${2}\times {10}^{{8}}$ cycles is obtained in the neuron. TCAD simulations further verify the scaling capability of the Z2-FET neuron and its energy consumption is estimated. The results suggest that $\text{Z}^{\vphantom {D^{f}}{2}}$ -FET has great potential for highly compact and energy-efficient artificial spiking neurons.
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