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A new locally active memristive synapse-coupled neuron model

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Abstract

In this paper, a new type of non-volatile locally active memristor with bi-stability is proposed by injecting appropriate voltage pulses to realize a switching mechanism between two stable states. It is found that the memristive parameters of the new memristor can affect the local activity, which has been rarely reported, and this phenomenon is explained based on mathematical analyses and numerical simulations. Then, a locally active memristive coupled neuron model is constructed using the proposed memristor as a connecting synapse. The parameter-associated dynamical behaviors are revealed by bifurcation plots, phase plane portraits and dynamical evolution maps. Moreover, the bi-stability phenomenon of the new coupled neuron model is disclosed by local attraction basins, and the periodic burster and multi-scroll chaotic burster are found if a multi-level pulse current is used to imitate a periodical external stimulus on the neurons. The Hamiltonian energy function is calculated and analyzed with or without external excitation. Finally, the neuronal circuit is designed and implemented, which can mimic electrical activity of the neurons and is useful for physical applications. The experimental results captured from the analog circuit are consistent well with the numerical simulation results.

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Data availability statement

Data will be made available on reasonable request.

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Acknowledgements

This work was partially supported by the Natural Science Foundation of Tianjin (No. 18JCYBJC87700), the New Generation Artificial Intelligence Technology Major Project of Tianjin (18ZXZNSY00270) and South African National Research Foundation Grants (Nos. 114911 and 132797).

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Authors and Affiliations

  1. Tianjin Key Laboratory For Control Theory and Applications in Complicated Systems, Tianjin University of Technology, Tianjin, 300384, China

    Ronghao Li & Enzeng Dong

  2. Department of Electrical and Mining Engineering, University of South Africa, Florida, 1710, South Africa

    Zenghui Wang

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  1. Ronghao Li
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  2. Zenghui Wang
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Correspondence to Enzeng Dong.

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Li, R., Wang, Z. & Dong, E. A new locally active memristive synapse-coupled neuron model. Nonlinear Dyn 104, 4459–4475 (2021). https://doi.org/10.1007/s11071-021-06574-1

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