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As research progresses, attention has been paid to the effects of the LIF neuron model and the leaky factor on SNN robustness. Among them, the LIF model is the most common SNN neuron model and the leaky factor is the signature parameter of LIF neurons. 2020, S. Sharmin [4] et al. demonstrated the potential of LIF neurons to be noise-resistant, and they pointed out that the leakage parameter is an additional knob to control the noise resistance of the model based on the effect of the inherent structural parameters of LIF neurons on the accuracy of the model. In 2021, S. S. Chowdhury [5] et al. investigated the role played by leakage in SNNs and concluded from frequency domain analysis that leakage can filter high frequency components thus improving model robustness. However, this field still needs a lot of theoretical and experimental support to explore highly robust SNNs and optimize neuronal models.
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IEEE/ICACT20230030 Slide.04
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