基于FDSOI的无复位电路LIF神经元的设计与研究

V. Rajakumari, S. Panda, K. P. Pradhan
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引用次数: 0

摘要

在这篇文章中,一个基于fdsoi的神经元被证明可以模拟LIF神经元的功能。由于所提出的基于器件的神经元利用单晶体管锁存器(STL)机制,并且以尖峰的形式接收电流输入和电压输出,因此不需要任何额外的电路进行复位。此外,所提出的神经元显示出令人印象深刻的每尖峰能量消耗,即在500 nA以下的所有输入值下,小于0.11 pJ/尖峰。有趣的是,它在MHz范围内显示出峰值频率,比生物神经元高约5个数量级。因此,基于fdsoi的LIF神经元具有较高的频率、能量和面积效率,与生物神经元相当,并且与CMOS工艺兼容,因此更适合于峰值神经网络(SNN)的大规模硬件实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
1T FDSOI Based LIF Neuron Without Reset Circuitry: A proposal and Investigation
In this article, an FDSOI-based neuron is demonstrated to mimic the functionalities of LIF neuron. As the proposed device-based neuron utilizes the single transistor latch (STL) mechanism and it takes the current input and voltage output in the shape of a spike, it does not require any extra circuit for reset. Furthermore, the proposed neuron shows an impressive energy consumption per spike i.e., less than 0.11 pJ/spike for all input values under 500 nA. Interestingly, it shows a spiking frequency in MHz range, which is ~5 orders greater than the biological neuron. Hence, due to its high frequency, energy and area efficiency, equivalent to that of a biological neuron and compatibility with CMOS process, the proposed FDSOI-based LIF neuron is more appropriate for large-scale hardware implementation of a spiking neural network (SNN).
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