Neural networks are favored by academia and industry because of their diversity of
dynamics. However, it is difficult for ring neural networks to generate complex dynamical …

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 brief presents a novel method to generate-scroll chaotic attractors. First, a magnetized
Hopfield neural network (HNN) with three neurons is modeled by introducing an improved …

Due to the synapse-like nonlinearity and memory characteristics, memristor is often used to
construct memristive neural networks with complex dynamical behaviors. However …

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 …

Nowadays, research, modeling, simulation and realization of brain-like systems to
reproduce brain behaviors have become urgent requirements. In this paper, neural bursting …

This paper aims to propose a novel no-equilibrium Hindmarsh–Rose (HR) neuron model
with memristive electromagnetic radiation effect. Compared with other memristor-based HR …

Hopfield neural networks are favored by academia and industrial fields due to their
abundant dynamics. In this paper, the dynamical behavior of a small Hopfield neural …

Circuit realization of neural networks is a significant approach in neuromorphic computing.
Researchers have simplified the circuit for single neuron model, but one for neural network …

Locally active memristor has become a research hotspot, and plays an important role in the
research of neural networks. In order to study the dynamic behavior of synaptic crosstalk …