Scroll-Growth and Scroll-Control Attractors in Memristive Bi-Neuron Hopfield Neural Network

Electromagnetic induction (EMI) is an external interference in electrophysiological environment, which can be characterized by a flux-controlled memristor. By replacing external stimulation with EMI current, this brief presents a 3D memristive bi-neuron Hopfield neural network (MBN-HNN). MBN-HNN has a line equilibrium set and produces multi-scroll chaotic attractors with scroll-growth over time. Further, a scroll- control method is proposed by nesting a saturation function into MBN-HNN and multi-scroll chaotic attractors with controllable scrolls are displayed. Besides, STM32 hardware experiments confirm numerical simulations.