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

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.