Laboratoire de Physique des Solides, UMR8502 CNRS - Université Paris-Sud, Université Paris-Saclay, 91405, Orsay, Cedex, France.
Laboratoire Génie électrique et électronique de Paris, CentraleSupélec, UMR8507 CNRS - Sorbonne Université, Université Paris-Saclay, 91192, Gif-sur-Yvette, Cedex, France.
Sci Rep. 2019 Jul 31;9(1):11123. doi: 10.1038/s41598-019-47348-5.
We introduce an ultra-compact electronic circuit that realizes the leaky-integrate-and-fire model of artificial neurons. Our circuit has only three active devices, two transistors and a silicon controlled rectifier (SCR). We demonstrate the implementation of biologically realistic features, such as spike-frequency adaptation, a refractory period and voltage modulation of spiking rate. All characteristic times can be controlled by the resistive parameters of the circuit. We built the circuit with out-of-the-shelf components and demonstrate that our ultra-compact neuron is a modular block that can be associated to build multi-layer deep neural networks. We also argue that our circuit has low power requirements, as it is normally off except during spike generation. Finally, we discuss the ultimate ultra-compact limit, which may be achieved by further replacing the SCR circuit with Mott materials.
我们介绍了一种超紧凑的电子电路，它实现了人工神经元的漏电积分和放电模型。我们的电路仅使用三个有源器件，两个晶体管和一个可控硅整流器（SCR）。我们展示了生物现实特征的实现，例如尖峰频率适应，不应期和尖峰率的电压调制。所有特征时间都可以通过电路的电阻参数来控制。我们使用现成的组件构建了该电路，并证明了我们的超紧凑神经元是一个模块化的模块，可以与其他模块组合来构建多层深度神经网络。我们还认为，我们的电路功耗很低，因为它通常处于关闭状态，除非在产生尖峰时才会打开。最后，我们讨论了最终的超紧凑极限，通过进一步用莫特材料代替 SCR 电路可能实现这一极限。
