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 …
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 …
Privacy protection of medical data based on multi-scroll memristive Hopfield neural network
F Yu, H Shen, Q Yu, X Kong… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Memristive Hopfield neural network (MHNN) has complex dynamic behavior, which is
suitable for encryption applications. In order to ensure the information security of the medical …
suitable for encryption applications. In order to ensure the information security of the medical …
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 …
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 …
Initial offset boosting coexisting attractors in memristive multi-double-scroll Hopfield neural network
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 …
In this paper, by introducing a non-ideal flux-controlled memristor model into a Hopfield …
Model of electrical activity in a neuron under magnetic flow effect
The electric activities of neurons are dependent on the complex electrophysiological
condition in neuronal system, and it indicates that the complex distribution of …
condition in neuronal system, and it indicates that the complex distribution of …
A multi-stable memristor and its application in a neural network
Nowadays, there is a lot of study on memristor-based systems with multistability. However,
there is no study on memristor with multistability. This brief constructs a mathematical …
there is no study on memristor with multistability. This brief constructs a mathematical …
A new class of Hopfield neural network with double memristive synapses and its DSP implementation
T Ma, J Mou, H Yan, Y Cao - The European Physical Journal Plus, 2022 - Springer
The nonlinear characteristics are studied in a new 4D Hopfield neural network model with
two nonlinear synaptic weights in this paper. The synaptic function is modeled by …
two nonlinear synaptic weights in this paper. The synaptic function is modeled by …
Coexisting multi-stable patterns in memristor synapse-coupled Hopfield neural network with two neurons
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 …
current appears in the Hopfield neural network (HNN), which can be emulated by a flux …