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Accuracy evaluation of numerical methods used in state-of-the-art simulators for spiking neural networks

机译：用于尖峰神经网络的最新仿真器中使用的数值方法的准确性评估

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摘要

With the various simulators for spiking neural networks developed in recent years, a variety of nu merical solution methods for the underlying differential equations are available. In this article, we introduce an approach to systematically assess the accuracy of these methods. In contrast to previous investigations, our approach focuses on a completely deterministic comparison and uses an analytically solved model as a reference. This enables the identification of typical sources of numerical inaccuracies in state-of-the-art simulation methods. In particular, with our approach we can separate the error of the numerical integration from the timing error of spike detection and propa gation, the latter being prominent in simulations with fixed timestep. To verify the correctness of the testing procedure, we relate the numerical deviations to the oretical predictions for the employed numerical meth ods. Finally, we give an example of the influence of simulation artefacts on network behaviour and spike timing-dependent plasticity (STDP), underlining the importance of spike-time accuracy for the simulation of STDP.
机译：近年来，随着各种用于加标神经网络的仿真器的出现，针对底层微分方程的各种数值解法均可用。在本文中，我们介绍了一种系统地评估这些方法的准确性的方法。与以前的研究相比，我们的方法侧重于完全确定性的比较，并使用解析解决的模型作为参考。这使得能够在最新的仿真方法中识别出典型的数值不准确来源。尤其是，通过我们的方法，我们可以将数值积分的误差与尖峰检测和传播的定时误差分开，后者在固定时间步长的仿真中很突出。为了验证测试程序的正确性，我们将数值偏差与所采用数值方法的矿石预测相关联。最后，我们给出了仿真伪像对网络行为和与峰值时序相关的可塑性（STDP）的影响的示例，强调了峰值时间精度对于STDP仿真的重要性。

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  • 来源
    《Journal of Computational Neuroscience》 |2012年第2期|p.309-326|共18页
  • 作者

    Stephan Henker; Johannes Partzsch; Rene Schueffny;

  • 作者单位

    Endowed Chair for Parallel VLSI Systems and Neural Circuits Institute of Circuits and Systems,University of Technology Dresden, Dresden, Germany;

    Endowed Chair for Parallel VLSI Systems and Neural Circuits Institute of Circuits and Systems,University of Technology Dresden, Dresden, Germany;

    Endowed Chair for Parallel VLSI Systems and Neural Circuits Institute of Circuits and Systems,University of Technology Dresden, Dresden, Germany;

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  • 正文语种 eng
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  • 关键词

    neural network simulation; numerical accuracy; integrate-and-fire; STDP;

    机译：神经网络仿真;数值精度整合并开火;STDP;

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