沟槽
神经元
材料科学
Spike(软件开发)
电压
尖峰神经网络
光电子学
计算机科学
电气工程
物理
人工神经网络
纳米技术
神经科学
工程类
人工智能
生物
图层(电子)
软件工程
标识
DOI:10.1109/tnano.2023.3278537
摘要
In this paper, using calibrated 2-D TCAD simulations we report a trench Bipolar I-MOS for the realization of a spiking neural network. We demonstrated that the proposed trench Bipolar I-MOS LIF neuron can emulate the biological neuronal nature and exhibits a low threshold voltage (-0.16 V), which is ∼ |400 mV| lower than the past reported LBIMOS LIF neuron. Moreover, the trench Bipolar I-MOS neuron consumes 0.35 pJ energy per spike, which is ∼ 100x lower in comparison to the PDSOI LIF neuron. Further, the proposed LIF neuron shows ∼ 10x reduction in energy per spike than the recently published Ge MOSFET and JLFET based LIF neurons. In addition, the proposed trench Bipolar I-MOS LIF neuron exhibits ∼ 6 orders high spiking frequency than the biological neuron. Also, the proposed device shows a ∼ 1.1x reduction in the breakdown voltage as compared to the conventional Bipolar I-MOS. This is due to the crowding of the electric field near the gate edges.
科研通智能强力驱动
Strongly Powered by AbleSci AI