Heterogeneous Neural Network: Hidden Firing Patterns, Phase Synchronization and Multistability

In this paper, a novel heterogeneous neural network is proposed by coupling improved memristor 2D HR neuron and 1D HNN neuron with locally active memristor. The effect of coupling intensity on synchronization behavior is analyzed. The results show that the increase in coupling intensity will lead to phase synchronization of the system. The coexistence of the firing pattern caused by the initial enhancement of the memristor is quantitatively analyzed and numerically simulated by introducing a multistable auto memristor. The results show that the newly constructed heterogeneous neural network exhibits an attractor bias pattern that enhances the initial migration behavior of the memristor, and these patterns have extreme multi-stability.