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| Bifurcation and Clustering Characteristics of Morris-lecar Neural System Under Electromagnetic Excitation |
| WANG Qixiaa, LI Xinyingb, GUO Wenhuib
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| a. School of Mathematics and Physics; b. School of Electronic Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China |
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Abstract Magnetronic memristor is introduced into the Morris-Lecar neural system to describe the induced current induced by magnetic flux, and the effect of memristor parameters on the dynamical characteristics of the system is explored. Based on the relationship between charge and magnetic flux, a memristive Morris-Lecar neuron model is established, the discharge patterns of the system are numerically simulated, and the synchronization transition process of the coupled system is researched by using the similarity function, and it is concluded that the strength of the electric coupling and the memristor parameters have a modulating effect on the synchronization state of the system. An asymmetric locally coupled memristive neural network model is constructed, and the effect of coupling strength on the existence of neural network embedded states is researched by using spatio-temporal dynamical diagrams, which further reveals the intrinsic mechanism of the information encoding and transmission process of complex neural network systems.
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Received: 20 November 2023
Published: 09 October 2025
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