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 …
Memristor initial-offset boosting in memristive HR neuron model with hidden firing patterns
A new three-dimensional (3D) memristive HR neuron model is presented, which is improved
from an existing memristive HR neuron model using a memristor synapse with sine …
from an existing memristive HR neuron model using a memristor synapse with sine …
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 …
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 …
A triple-memristor Hopfield neural network with space multistructure attractors and space initial-offset behaviors
Memristors have recently demonstrated great promise in constructing memristive neural
networks with complex dynamics. This article proposes a memristive Hopfield neural …
networks with complex dynamics. This article proposes a memristive Hopfield neural …
Two-dimensional memristive hyperchaotic maps and application in secure communication
Continuous memristor has been widely used in chaotic oscillating circuits and neuromorphic
computing systems. However, discrete memristor and its coupling discrete map have not …
computing systems. However, discrete memristor and its coupling discrete map have not …
Dynamics analysis, synchronization and FPGA implementation of multiscroll Hopfield neural networks with non-polynomial memristor
F Yu, X Kong, W Yao, J Zhang, S Cai, H Lin… - Chaos, Solitons & …, 2024 - Elsevier
The number of attractors in a memristor-based multiscroll Hopfield Neural Network (HNN) is
typically coupled with the number of polynomials, which leads to a coupling between the …
typically coupled with the number of polynomials, which leads to a coupling between the …
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 …
Memristor initial-offset boosting and its bifurcation mechanism in a memristive FitzHugh-Nagumo neuron model with hidden dynamics
Electromagnetic induction plays a vital role in impacting the neuron dynamics, since the
electromagnetic induction is triggered alongside with the complex interaction of membrane …
electromagnetic induction is triggered alongside with the complex interaction of membrane …
Locally active memristor-based neuromorphic circuit: Firing pattern and hardware experiment
Analog circuit implementation of neuron model is an essential category of neuromorphic
circuit since it can reproduce neuron firing patterns and assist in exploring neuron-based …
circuit since it can reproduce neuron firing patterns and assist in exploring neuron-based …