Sufficient condition for identical synchronization in complete network of ordinary differential equations of the Hindmarsh – Rose 3D type with linear coupling
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Tóm tắt
This paper examines identical synchronization in a complete network consisting of nodes. Each node is connected to every other node through linear coupling and is represented by ordinary differential equations of the Hindmarsh-Rose 3D type, which can be derived from the well-known Hodgkin-Huxley model. The study establishes a sufficient condition regarding the coupling strength necessary to achieve the desired synchronization. The findings indicate that networks with higher in-degrees for the nodes synchronize more readily. Additionally, the paper presents numerical simulations in C++ to support this theoretical result, highlighting the existence of a trade-off.
Từ khóa
complete network, coupling strength, Hindmarsh-Rose 3D type, identical synchronization, linear coupling, ordinary differential equations
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Tài liệu tham khảo
Ambrosio, B., & Aziz-Alaoui, M. A. (2012). Synchronization and control of coupled reaction-diffusion systems of the FitzHugh-Nagumo-type. Computers and Mathematics with Applications, 64, 934-943.
Ambrosio, B., & Aziz-Alaoui, M. A. (2013). Synchronization and control of a network of coupled reaction-diffusion systems of generalized FitzHugh-Nagumo type. ESAIM: Proceedings, Vol. 39, p. 15-24.
Aziz-Alaoui, M. A. (2006). Synchronization of Chaos. Encyclopedia of Mathematical Physics, Elsevier, Vol. 5, pp : 213-226.
Corson, N. (2009). Dynamique d'un modèle neuronal, synchronisation et complexité. PhD thesis, University of Le Havre, France.
Ermentrout, G. B., & Terman, D. H. (2009). Mathematical foundations of neurosciences. Springer.
Hodgkin, A. L., & Huxley, A. F. (1952). A quantitative description of membrane current and ts application to conduction and excitation in nerve. J. Physiol., 117, 500-544.
Izhikevich, E. M. (2007). Dynamical systems in neuroscience. The MIT Press.
Keener, J. P., & Sneyd, J. (2009). Mathematical physiology. Springer.
Murray, J. D. (2010). Mathematical biology. Springer.
Nagumo, J., Arimoto, S., & Yoshizawa, S. (1962). An active pulse transmission line simulating nerve axon. Proc. IRE. 50, 2061-2070.