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Dynamics analysis and FPGA implementation of Discrete-time Fractional-order memcapacitor-based Hopfield neural network

Author

Listed:
  • Li, Yufei
  • Zhu, Jiayi
  • Wang, Chunhua

Abstract

As a biomimetic component, the memcapacitor has been increasingly applied in brain-like dynamics research. Based on this, this paper proposes a discrete-time fractional-order memcapacitor for the first time and uses it as electromagnetic radiation in a three-dimensional fractional-order discrete-time Hopfield neural network (HNN). Firstly, the charge–voltage hysteresis loop characteristics of the memcapacitor at a specified order are studied. Then, the five-dimensional system after radiation is investigated using bifurcation diagrams, phase diagrams, Lyapunov exponent diagrams, etc., and various dynamical behaviors such as hyperchaos, coexistence of attractors, attractor expansion, symmetric attractors, and hidden attractors are discovered based on the changes of three parameters. Finally, the system is implemented on Field-Programmable Gate Array (FPGA) using the truncation method for the Caputo operator, its feasibility has been demonstrated.

Suggested Citation

  • Li, Yufei & Zhu, Jiayi & Wang, Chunhua, 2026. "Dynamics analysis and FPGA implementation of Discrete-time Fractional-order memcapacitor-based Hopfield neural network," Chaos, Solitons & Fractals, Elsevier, vol. 208(P4).
    • Handle: RePEc:eee:chsofr:v:208:y:2026:i:p4:s0960077926005059
    DOI: 10.1016/j.chaos.2026.118364
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