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<p>Due to their biomimetic characteristics, memcapacitors have attracted increasing attention in the field of neuromorphic computing. This paper proposes a memcapacitive Hopfield neural network model utilizing a novel multi-segment memcapacitor as the source of electromagnetic radiation. First, the equilibrium points of the system are analyzed. By adjusting the internal parameters of the memcapacitor, the system can flexibly generate a controllable number of multi-scroll chaotic attractors. Dynamical analysis reveals that under different initial conditions, the system can exhibit coexistence of heterogeneous attractors as well as homogeneous attractors symmetric about the origin. Additionally, specific parameters enable approximately linear amplitude control of the attractors, and changing initial conditions can induce initial offset boosting behavior, further enriching the system’s multistability. Subsequently, to bridge theory and hardware, an FPGA-based hardware platform is implemented. The experimental results demonstrate that the proposed system successfully realizes multi-scroll attractors, offset boosting, and amplitude control with low resource utilization, in close agreement with numerical simulations. Finally, the system is applied to design a PRNG. The statistical randomness verified by NIST SP800-22 tests highlights its great potential for secure communication and encryption applications.</p>

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Dynamics analysis and FPGA implementation of multi-scroll chaotic attractors in memcapacitor-based Hopfield neural network

  • 期刊论文

  • 发表日期：

    2026年6月24日

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  • Dongbin Wang,
  • Chunhua Wang,
  • Gang Yang,
  • Quanli Deng

摘要

Due to their biomimetic characteristics, memcapacitors have attracted increasing attention in the field of neuromorphic computing. This paper proposes a memcapacitive Hopfield neural network model utilizing a novel multi-segment memcapacitor as the source of electromagnetic radiation. First, the equilibrium points of the system are analyzed. By adjusting the internal parameters of the memcapacitor, the system can flexibly generate a controllable number of multi-scroll chaotic attractors. Dynamical analysis reveals that under different initial conditions, the system can exhibit coexistence of heterogeneous attractors as well as homogeneous attractors symmetric about the origin. Additionally, specific parameters enable approximately linear amplitude control of the attractors, and changing initial conditions can induce initial offset boosting behavior, further enriching the system’s multistability. Subsequently, to bridge theory and hardware, an FPGA-based hardware platform is implemented. The experimental results demonstrate that the proposed system successfully realizes multi-scroll attractors, offset boosting, and amplitude control with low resource utilization, in close agreement with numerical simulations. Finally, the system is applied to design a PRNG. The statistical randomness verified by NIST SP800-22 tests highlights its great potential for secure communication and encryption applications.