An ultra-compact leaky-integrate-and-fire model for building spiking neural networks
An ultra-compact leaky-integrate-and-fire model for building spiking neural networks
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DOI：
10.1038/s41598-019-47348-5
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发表时间：
2019-07-31
影响因子：
4.6
通讯作者：
Stoliar, P.
中科院分区：
文献类型：
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作者：
Rozenberg, M. J.;Schneegans, O.;Stoliar, P.
我们介绍了一个超紧凑的电子电路，实现了人工神经元的漏集成和火灾模型。我们的电路只有三个有源器件，两个晶体管和一个可控硅整流器（SCR）。我们演示了实现生物现实的功能，如尖峰频率适应，不应期和电压调制的尖峰率。所有的特征时间都可以通过电路的电阻参数来控制。我们用现成的组件构建了电路，并证明了我们的超紧凑神经元是一个模块化块，可以关联起来构建多层深度神经网络。我们还认为，我们的电路具有低功耗要求，因为它通常是关闭的，除了在尖峰生成。最后，我们讨论了最终的超紧凑极限，这可能是通过进一步取代的SCR电路莫特材料。
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.