Review on memristor application in neural circuit and network

F Yang, J Ma, F Wu - Chaos, Solitons & Fractals, 2024 - Elsevier
Memristor is a nonlinear electronic component with memory properties, it is widely used in a
variety of nonlinear circuits for extensive adaptive control and model description of neural …

The future of memristors: Materials engineering and neural networks

K Sun, J Chen, X Yan - Advanced Functional Materials, 2021 - Wiley Online Library
Abstract From Deep Blue to AlphaGo, artificial intelligence and machine learning are
booming, and neural networks have become the hot research direction. However, due to the …

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 …

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 …

Memristor synapse-coupled piecewise-linear simplified Hopfield neural network: Dynamics analysis and circuit implementation

S Ding, N Wang, H Bao, B Chen, H Wu, Q Xu - Chaos, Solitons & Fractals, 2023 - Elsevier
Electromagnetic induction current is generated between the adjacent neurons in neural
network caused by the existence of membrane potential difference. Memristor is the fourth …

Hyperchaotic memristive ring neural network and application in medical image encryption

H Lin, C Wang, L Cui, Y Sun, X Zhang, W Yao - Nonlinear dynamics, 2022 - Springer
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 …

Review on chaotic dynamics of memristive neuron and neural network

H Lin, C Wang, Q Deng, C Xu, Z Deng, C Zhou - Nonlinear Dynamics, 2021 - Springer
The study of dynamics on artificial neurons and neuronal networks is of great significance to
understand brain functions and develop neuromorphic systems. Recently, memristive …

A review of chaotic systems based on memristive Hopfield neural networks

H Lin, C Wang, F Yu, J Sun, S Du, Z Deng, Q Deng - Mathematics, 2023 - mdpi.com
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 …

Offset-control plane coexisting behaviors in two-memristor-based Hopfield neural network

H Bao, M Hua, J Ma, M Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
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 …

A memristive synapse control method to generate diversified multistructure chaotic attractors

H Lin, C Wang, C Xu, X Zhang… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Due to the synapse-like nonlinearity and memory characteristics, memristor is often used to
construct memristive neural networks with complex dynamical behaviors. However …