IC neuron: An efficient unit to construct neural networks

An, Junyi; Liu, Fengshan; Shen, Furao; Zhao, Jian; Li, Ruotong; Gao, Kepan

doi:10.1016/j.neunet.2021.10.005

Cited by 4 publications

(1 citation statement)

References 19 publications

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“…These spiking neuron models have been incorporated into deep learning as spiking neural networks (SNNs), which have shown great potential in dealing with complex recognition and prediction tasks due to their rich temporal dynamics [22]. In addition, novel neuron models, such as the FitzHugh-Nagumo neuron model, which considers the spiking and bursting behaviors of a neuron, and the inter-layer collision neuron model, inspired by physical elastic collision scenes, have also been developed [23,24]. These third-generation neuronal models are still in the research field and are less well known outside academia, as they have not yet been commercially converted [25].…”

Section: Introductionmentioning

confidence: 99%

Yet Another Effective Dendritic Neuron Model Based on the Activity of Excitation and Inhibition

Yang

Li²,

et al. 2023

Mathematics

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Neuronal models have remained an important area of research in computer science. The dendritic neuron model (DNM) is a novel neuronal model in recent years. Previous studies have focused on training DNM using more appropriate algorithms. This paper proposes an improvement to DNM based on the activity of excitation and proposes three new models. Each of the three improved models are designed to mimic the excitation and inhibition activity of neurons. The improved model proposed in this paper is shown to be effective in the experimental part. All three models and original DNM have their own strengths, so it can be considered that the new model proposed in this paper well enriches the diversity of neuronal models and contributes to future research on networks models.

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