The feed-forward neural networks are the basis and have been widely applied on modern deep learning models, wherein connection strength between neurons plays a critical role in weak signal propagation and neural synchronization. In this paper, a four-variable Hindmarsh–Rose (HR) neural model is presented by introducing an additive variable as magnetic flow which changes the membrane potential via a memristor. The improved HR neurons in the feed-forward multilayer (four and eight layers) networks are investigated. The effects of electromagnetic...
