Coupling dynamics in an FHN bi-neuron model coupled via ReLU function-based locally active memristor-Reference-Cited by-同舟云学术

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Coupling dynamics in an FHN bi-neuron model coupled via ReLU function-based locally active memristor

Published:2024-08-12 Issue: Volume: Page:
ISSN:0924-090X
Container-title:Nonlinear Dynamics
language:en
Short-container-title:Nonlinear Dyn

Author:

Chen Xiongjian^ORCID,Wang Ning^ORCID,Wang Kai,Chen Mo^ORCID,Parastesh Fatemeh^ORCID,Xu Quan^ORCID

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Scientific Research Foundation of Jiangsu Provincial Education Department, China

Centre for Nonlinear Systems, Chennai Institute of Technology, India

Project 333 of Jiangsu Province

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11071-024-10127-7.pdf

Reference59 articles.

1. Sun, J., Wang, Y., Liu, P., Wen, S., Wang, Y.: Memristor-based neural network circuit with multimode generalization and differentiation on Pavlov associative memory. IEEE Trans. Cybern. 53(5), 3351–3362 (2022)

2. Yang, Y., Ma, J., Xu, Y., Jia, Y.: Energy dependence on discharge mode of Izhikevich neuron driven by external stimulus under electromagnetic induction. Cogn. Neurodyn. 15, 265–277 (2021)

3. Ma, J.: Biophysical neurons, energy, and synapse controllability: a review. J. Zhejiang Univ-Sci. A 24(2), 109–129 (2023)

4. Hodgkin, A.L., Huxley, A.F.: A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Physiol. 117(4), 500 (1952)

5. Zhu, Z., Wang, R., Zhu, F.: The energy coding of a structural neural network based on the Hodgkin–Huxley model. Front. Neurosci. 12, 306922 (2018)

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