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A novel hardware-efficient spiking neuron model based on asynchronous cellular automaton dynamics exhibiting various nonlinear response curves

机译:基于异步细胞自动机动力学的新型硬件效率增强神经元模型,具有多种非线性响应曲线

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In this paper, a novel hardware-efficient spiking neuron model based on an asynchronous cellular automaton is proposed. It is shown that the proposed model can exhibit typical nonlinear response curves (so-called IF-curves) such as class 1 excitability without hysteresis, class 2 excitability without hysteresis, and class 2 excitability and class 1 spiking with hysteresis. The proposed model is implemented by an FPGA device and it is shown that the FPGA-implemented proposed model can exhibit the typical nonlinear response curves. Furthermore, it is shown that the proposed model can be implemented by much fewer circuit elements compared to some conventional neuron models that exhibit the typical nonlinear response curves.
机译:本文提出了一种基于异步细胞自动机的新型硬件效率高的突跳神经元模型。结果表明,所提出的模型可以表现出典型的非线性响应曲线(所谓的IF曲线),如无滞后的1类励磁,无滞后的2类励磁,具有滞后的2类励磁和1类尖峰。所提出的模型是由FPGA器件实现的,结果表明,由FPGA实施的提出的模型可以表现出典型的非线性响应曲线。此外,表明与具有典型非线性响应曲线的一些常规神经元模型相比,所提出的模型可以用更少的电路元件来实现。

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