Multistable State of Six Dimensional Memristor HR Neuron Model and Its Hardware Implementation

This paper proposes a new six dimensional memristor HR neuron model, the model is an improvement to the existing memristor HR model. It uses a cosine memristor and a sine memristor in neurons, respectively for the coupling and electromagnetic induction coupling. The model has no equilibrium point. Through the phase diagram and the bifurcation diagram, the Lyapunov index spectrum analyses its dynamic behavior, finding an improved memristor HR neuron model can show the boosting behavior, and changing the initial value of memristor can produce firing pattern booster to different discrete levels. The dissipation of the proposed model is studied. These patterns are homogeneous with extreme stability. Finally, the simulation results could be captured through the stm32 implementation and the oscilloscope. The results agree with the theoretical analysis.