Dynamical behavior of ring-star neural networks with small-world characteristics

Abstract This paper proposes a ring-star neural network with small-world characteristics (RS-SWNN) based on the classical ring-star network, and combines the Izhikevich neuron model. RS-SWNN incorporates small-world characteristics, better mimicking the non-uniform connectivity of biological neural networks. According to the different coupling strength settings of D ring and D star , the dynamical behavior of the network is studied, and the synchronicity differences of the network under different coupling strengths are revealed. In addition, a discrete memristor is used to simulate the effects of electromagnetic radiation. The modulation effects of varying radiation intensities on the network synchronization are further analyzed. The study shows that the electromagnetic radiation effect significantly impacts the neuronal synchronization behavior, especially in its modulation of network synchronization under varying coupling strengths. Numerical simulation is carried out using MATLAB software, and the corresponding results are obtained.

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Publication Details

Journal
Chinese Physics B
Published
2025-05-29
DOI
https://doi.org/10.1088/1674-1056/adde39
Citations
3
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
7.44
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article

Dynamical behavior of ring-star neural networks with small-world characteristics

Shaobo 少波 He 贺, Minglin 铭磷 Ma 马, Umme Kalsoom, Zhiyi 芷依 Yuan 袁 et al.
3 citations
Chinese Physics B
Neural Networks and Applications
7.44
article

Dynamical behavior of ring-star neural networks with small-world characteristics

Shaobo 少波 He 贺, Minglin 铭磷 Ma 马, Umme Kalsoom, Zhiyi 芷依 Yuan 袁, Weizheng 为政 Deng 邓
article en
3 citations

Abstract

Abstract This paper proposes a ring-star neural network with small-world characteristics (RS-SWNN) based on the classical ring-star network, and combines the Izhikevich neuron model. RS-SWNN incorporates small-world characteristics, better mimicking the non-uniform connectivity of biological neural networks. According to the different coupling strength settings of D ring and D star , the dynamical behavior of the network is studied, and the synchronicity differences of the network under different coupling strengths are revealed. In addition, a discrete memristor is used to simulate the effects of electromagnetic radiation. The modulation effects of varying radiation intensities on the network synchronization are further analyzed. The study shows that the electromagnetic radiation effect significantly impacts the neuronal synchronization behavior, especially in its modulation of network synchronization under varying coupling strengths. Numerical simulation is carried out using MATLAB software, and the corresponding results are obtained.

Chinese Physics BVol. 34(10)
Nara University (JP)
Openalex Percentile: Top 3%
Neural Networks and Applications
7.44
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