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

机译:一种基于异步蜂窝自动机动态的新型硬件有效的尖峰神经元模型,其呈现各种非线性响应曲线

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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蜂窝自动机的新型硬件有效的尖峰神经元模型。结果表明,该模型可以表现出典型的非线性响应曲线(所谓的If-曲线),例如1类兴奋性,没有滞后,2级兴奋性,没有滞后,2类兴奋性和滞后性1类兴奋性。所提出的模型由FPGA装置实现,并显示出FPGA实现的提出的模型可以表现出典型的非线性响应曲线。此外,示出了与具有典型非线性响应曲线的一些传统的神经元模型相比,所提出的模型可以通过更少的电路元件实现。

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