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Complex dynamics of a new multiscroll memristive neural network

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Abstract

In this paper, a cyclic memristive neural network structure is proposed. There are counterclockwise connections between the neurons. The system generates a controllable number of multi-scroll chaos by means of memristors with multi-segment nonlinear functions, which can produce a controllable infinite coexistence of heterogeneous attractors with initial offsets and a large range of amplitude-modulation properties. Through numerical simulations, the phenomenon of multi-scroll chaos is demonstrated and the coexisting attractors are found to exhibit extreme multi-stability as well as parameter-dependent amplitude-modulation properties. In addition, the feasibility of the system is verified by the construction of the circuit platform, the results of the digital hardware experiments are given, and the PRNG is constructed by applying this circular memristor neural network system.

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Acknowledgements

This work was partially supported by the National Natural Science Foundation of China under Grant 62366014 and the Jiangxi Provincial Natural Science Foundation under Grant 20232BAB202008.

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Authors and Affiliations

  1. East China Jiaotong University, Nanchang, 330013, China

    Yidan Chen, Qiang Lai & Yongxian Zhang

  2. Department of Computer Engineering Engineering Faculty, Karamanoglu Mehmetbey University, 70200, Karaman, Turkey

    Uǧur Erkan

  3. Department of Artificial Intelligence and Data Engineering, Engineering Faculty Ankara University, 06830, Ankara, Turkey

    Abdurrahim Toktas

Authors
  1. Yidan Chen
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  2. Qiang Lai
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  3. Yongxian Zhang
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  4. Uǧur Erkan
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  5. Abdurrahim Toktas
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All authors contributed to the study and writing of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Qiang Lai.

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Chen, Y., Lai, Q., Zhang, Y. et al. Complex dynamics of a new multiscroll memristive neural network. Nonlinear Dyn 112, 8603–8616 (2024). https://doi.org/10.1007/s11071-024-09466-2

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