Structure and analysis of memristive autapse spiking neuron with multistability and its implementation

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Abstract
Trying to understand the information transfer between neurons more clearly through synapses has been of great interest. In this work, a memristive autapse spiking (MAS) neuron is constructed by using discrete memristors as the autapse of neurons, combined with a discrete neuron mathematical model. Nonlinear theory plays an important role in the analysis of neural dynamics. Therefore, nonlinear numerical analysis methods, including time-domain waveforms trajectories in phase space and bifurcation behaviors, are used to analyze the basic dynamical behavior and complex multistability of MAS neuron. The complex dynamical behavior of the neuron mainly depends on the variation of the memristor parameters, and setting different parameters, the MAS neuron shows bi-stability and extreme multi-stability, which fully verifies the bionic behavior generated by the constructed MAS neuron. The implementation of MAS neuron is an important prerequisite for its application in engineering. Finally, a DSP experimental platform is built to successfully capture the attractor generated by the MAS neuron. This work provides new ideas for the construction and application of discrete neurons.
Funding Information
  • Liaoning Provincial Science and Technology Plan Joint Project (2024-MSLH-033)
  • Technological Innovation Projects (2023JH26)
  • Technological Innovation Projects (10300011)
  • Liaoning Province (LJ212410152049)

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