Abstract The biological Hodgkin–Huxley model and its simplified versions have confirmed its
effectiveness for recognizing and understanding the electrical activities in neurons, and …

Memristive electromagnetic induction effect has been widely explored in bi-neuron network
with homogeneous neurons, but rarely in bi-neuron network with heterogeneous ones. This …

Pattern estimation and selection in media can give important clues to understand the
collective response to external stimulus by detecting the observable variables. Both reaction …

Dynamical modeling of nervous systems is of fundamental importance in many scientific
fields containing the topics relative to computational neuroscience and biophysics. Many …

When synaptic connection is created to couple two neurons, the electromagnetic induction
current is unavoidably induced, which can be imitated by a flux-controlled memristor. To …

When possessing a potential difference between two neurons, an electromagnetic induction
current appears in the Hopfield neural network (HNN), which can be emulated by a flux …

The ion exchange in neurons can trigger time-varying magnetic fields. According to the
superposition field principle, each neuron is exposed to the integrated magnetic field …

Memristor synapse can be used to characterize the electromagnetic induction effect
between two neurons that induces an action current by their membrane potential difference …

This article addresses the investigation of strict dissipativity synchronization for a class of
static neural networks under an event-triggered scheme. An event-triggered scheme is …

Recently, discrete memristor maps can be directly constructed using discrete memristors.
However, some discrete memristors with reciprocal polynomial memristances cannot be …