The nervous system is made of a large number of neurons. Time-varying balance between
excitatory and inhibitory neurons is important to activate appropriate modes of electrical …

Played as an important nonlinear electric device, memristor is often used to build a variety of
nonlinear circuits, which can produce a variety of modes in oscillation. Due to the memory …

In this paper, a new method for generating symmetric multi-scroll attractors is proposed
based on a magnetized Hopfield neural network (HNN). Firstly, the mathematical model of …

It is believed that local activation is the origin of all complexities, and the locally active
memristive synaptic neural network can generate complex chaotic dynamic behaviors, such …

This paper proposes a kind of nonvolatile locally active memristor. The three fingerprints for
distinguishing memristor is verified by the stable and coexisting pinched hysteresis loops …

Memristors are widely considered to be promising candidates to mimic biological synapses.
In this paper, by introducing a non-ideal flux-controlled memristor model into a Hopfield …

Synapses can regulate the energy balance in the neural network. In this work, a two-neuron
network is established by coupling two Morris-Lecar neurons using a memristor synapse …

The theoretical, numerical and experimental demonstrations of firing dynamics in isolated
neuron are of great significance for the understanding of neural function in human brain. In …

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 …