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Multistable dynamics in a Hopfield neural network under electromagnetic radiation and dual bias currents

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Abstract

This paper investigates a Hopfield neural network under the simulation of external electromagnetic radiation and dual bias currents, in which the fluctuation of magnetic flux across the neuron membrane is used to emulate the influence of electromagnetic radiation. Utilizing conventional analytical methods, the basic properties of the proposed Hopfield neural network are discussed. Due to the addition of electromagnetic radiation and dual bias currents, the Hopfield neural network shows high sensitivity to system parameters and initial conditions. The proposed Hopfield neural network possesses multistability with periodic attractor, quasi-periodic attractor, chaotic attractor and transient chaotic attractor, and all of the attractors are hidden attractors because there is no equilibrium point in the system. In particular, when the neuron membrane magnetic flux is different, the system can present transient chaos with different chaotic times. More interestingly, with the change of system parameters, the proposed Hopfield neural network can exhibit parallel bifurcation behaviors. Finally, the Multisim simulation and hardware experiment results based on discrete electronic components are conducted to support the numerical ones. These results could give useful information to the study of nonlinear dynamic characteristics of the Hopfield neural network.

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Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on a reasonable request.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their constructive comments and insightful suggestions.

Funding

This work is supported by the National Natural Science Foundation of China (Grant No. 61901169) and the Natural Science Foundation of Hunan Province, China (Grant No. 2019JJ40190).

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Authors and Affiliations

  1. College of Information Science and Engineering, Hunan Normal University, Changsha, 410081, People’s Republic of China

    Qiuzhen Wan, Zidie Yan, Fei Li, Jiong Liu & Simiao Chen

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  1. Qiuzhen Wan
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Correspondence to Qiuzhen Wan.

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Wan, Q., Yan, Z., Li, F. et al. Multistable dynamics in a Hopfield neural network under electromagnetic radiation and dual bias currents. Nonlinear Dyn 109, 2085–2101 (2022). https://doi.org/10.1007/s11071-022-07544-x

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