Bipolar Pulse-induced Coexisting Symmetric Attractors in Hopfield Neural Network

By exerting a bipolar pulse (BP) current on one neuron, a non-autonomous Hopfield neural network (HNN) model is proposed in this paper, where complex dynamical effects of coexisting symmetric attractors are exhibited apparently. Firstly, using graphical method to calculate the switchable equilibrium points, we find that unstable node-focus (UNF) and stable node-focus (SNF) are existed in the model. Additionally, using multiple dynamical methods to reveal the initial-related bistable patterns, we find that the proposed model behaves coexisting symmetric attractors. Finally, we develop an electronic neuron circuit for the model on the analog level, and the PSIM-based circuit simulations excellently verify the numerical results.