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ASIC Oriented Comparative Analysis Of Biologically Inspired Neuron Models

机译:面向ASIC的生物启发神经元模型的比较分析

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This paper introduces the hardware and the ASIC implementations of the four most popular biologically inspired neuron models. The models are quartic, Izhikevich, Hindmarsh Rose and Fitzhugh-Nagumo. Moreover, some approximate computing techniques are applied on these models to reduce the area and power consumption. In addition, ASIC implementations of these models and their approximate versions are carried out. Also, spiking behavior error between these models and the Hodgkin Huxley model, the reference accurate model, is presented. Finally, a fair comparative analysis is discussed to help the Spiking Neural Networks designers to select the best neuron model hardware implementation from the power, area and accuracy perspectives.
机译:本文介绍了四种最受欢迎​​的受生物学启发的神经元模型的硬件和ASIC实现。这些模型是四次的,有Izhikevich,Hindmarsh Rose和Fitzhugh-Nagumo。而且,一些近似的计算技术被应用于这些模型以减小面积和功耗。此外,还将执行这些模型的ASIC实现及其近似版本。此外,还介绍了这些模型与参考准确模型Hodgkin Huxley模型之间的尖峰行为误差。最后,讨论了公平的比较分析,以帮助Spiking Neural Networks设计人员从功率,面积和准确性的角度选择最佳的神经元模型硬件实现。

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