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 …
High-dimensional memristive neural network and its application in commercial data encryption communication
With the development of economic globalization, demands for digital business data sharing
among different subsidiary companies are constantly emerging. How to achieve secure …
among different subsidiary companies are constantly emerging. How to achieve secure …
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 …
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 …
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 …
Memristive Hopfield neural network dynamics with heterogeneous activation functions and its application
Activation functions play a crucial in emulating biological neurons within artificial neural
networks. However, the exploration of neural networks composed of various activation …
networks. However, the exploration of neural networks composed of various activation …
Firing pattern in a memristive Hodgkin–Huxley circuit: Numerical simulation and analog circuit validation
Q Xu, Y Wang, B Chen, Z Li, N Wang - Chaos, Solitons & Fractals, 2023 - Elsevier
Spiking firing patterns and their hardware implementation can assist us in exploring spike-
based applications. The classical Hodgkin–Huxley circuit can generate spiking firing …
based applications. The classical Hodgkin–Huxley circuit can generate spiking firing …
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 …
Dynamical analysis of an improved FitzHugh-Nagumo neuron model with multiplier-free implementation
The cubic-polynomial nonlinearity with N-shaped curve plays a crucial role in generating
abundant electrical activities for the original FitzHugh-Nagumo (FHN) neuron model. The …
abundant electrical activities for the original FitzHugh-Nagumo (FHN) neuron model. The …
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 …