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 …
Biophysical neurons, energy, and synapse controllability: a review
J Ma - Journal of Zhejiang University-Science A, 2023 - Springer
Diffusive intracellular and extracellular ions induce a gradient electromagnetic field that
regulates membrane potential, and energy injection from external stimuli breaks the energy …
regulates membrane potential, and energy injection from external stimuli breaks the energy …
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 …
Symmetric multi-scroll attractors in magnetized Hopfield neural network under pulse controlled memristor and pulse current stimulation
Q Wan, F Li, S Chen, Q Yang - Chaos, Solitons & Fractals, 2023 - Elsevier
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 …
based on a magnetized Hopfield neural network (HNN). Firstly, the mathematical model of …
Memristive Rulkov neuron model with magnetic induction effects
The magnetic induction effects have been emulated by various continuous memristive
models but they have not been successfully described by a discrete memristive model yet …
models but they have not been successfully described by a discrete memristive model yet …
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 …
Dynamics analysis and hardware implementation of multi-scroll hyperchaotic hidden attractors based on locally active memristive Hopfield neural network
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 …
memristive synaptic neural network can generate complex chaotic dynamic behaviors, such …
A tristable locally active memristor and its application in Hopfield neural network
C Li, Y Yang, X Yang, X Zi, F Xiao - Nonlinear Dynamics, 2022 - Springer
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 …
distinguishing memristor is verified by the stable and coexisting pinched hysteresis loops …
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 …