Review on chaotic dynamics of memristive neuron and neural network
The study of dynamics on artificial neurons and neuronal networks is of great significance to
understand brain functions and develop neuromorphic systems. Recently, memristive …
understand brain functions and develop neuromorphic systems. Recently, memristive …
[HTML][HTML] A review of chaotic systems based on memristive Hopfield neural networks
Since the Lorenz chaotic system was discovered in 1963, the construction of chaotic
systems with complex dynamics has been a research hotspot in the field of chaos. Recently …
systems with complex dynamics has been a research hotspot in the field of chaos. Recently …
Design and analysis of multiscroll memristive hopfield neural network with adjustable memductance and application to image encryption
Q Lai, Z Wan, H Zhang, G Chen - IEEE Transactions on Neural …, 2022 - ieeexplore.ieee.org
Memristor is an ideal electronic device used as an artificial nerve synapse due to its unique
memory function. This article presents a design of a new Hopfield neural network (HNN) that …
memory function. This article presents a design of a new Hopfield neural network (HNN) that …
Brain-like initial-boosted hyperchaos and application in biomedical image encryption
Neural networks have been widely and deeply studied in the field of computational
neurodynamics. However, coupled neural networks and their brain-like chaotic dynamics …
neurodynamics. However, coupled neural networks and their brain-like chaotic dynamics …
Generating grid multi-scroll attractors in memristive neural networks
Q Lai, Z Wan, PDK Kuate - … on Circuits and Systems I: Regular …, 2022 - ieeexplore.ieee.org
Memristors are well suited as artificial nerve synapses owing to its unique memory function.
This paper establishes a novel flux-controlled memristor model using hyperbolic function …
This paper establishes a novel flux-controlled memristor model using hyperbolic function …
Hyperchaotic memristive ring neural network and application in medical image encryption
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 …
dynamics. However, it is difficult for ring neural networks to generate complex dynamical …
Memristor synapse-coupled piecewise-linear simplified Hopfield neural network: Dynamics analysis and circuit implementation
Electromagnetic induction current is generated between the adjacent neurons in neural
network caused by the existence of membrane potential difference. Memristor is the fourth …
network caused by the existence of membrane potential difference. Memristor is the fourth …
Offset-control plane coexisting behaviors in two-memristor-based Hopfield neural network
Memristor synapse with activated synaptic plasticity can be taken as an adaptive connection
synaptic weight. To demonstrate its kinetic effects, in this article, we present an improved …
synaptic weight. To demonstrate its kinetic effects, in this article, we present an improved …
Generating n-Scroll Chaotic Attractors From a Memristor-Based Magnetized Hopfield Neural Network
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 …
Hopfield neural network (HNN) with three neurons is modeled by introducing an improved …
A memristive synapse control method to generate diversified multistructure chaotic attractors
Due to the synapse-like nonlinearity and memory characteristics, memristor is often used to
construct memristive neural networks with complex dynamical behaviors. However …
construct memristive neural networks with complex dynamical behaviors. However …