Simple cyclic memristive neural networks with coexisting attractors and large-scale amplitude control

DOI10.1063/5.0153885MaRDI QIDQ6550023

Shicong Guo, Qiang Lai

Publication date: 4 June 2024

Published in: Chaos (Search for Journal in Brave)

zbMATH Keywords

controlneural networkattractor

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Analytic circuit theory (94C05) Complex behavior and chaotic systems of ordinary differential equations (34C28) Dynamical aspects of attractors and their bifurcations (37G35)

Related Items (1)

Heterogeneous coexisting attractors, large-scale amplitude control and finite-time synchronization of central cyclic memristive neural networks

Cites Work

• Dynamic behaviors of a class of memristor-based Hopfield networks
• Coexisting multi-stable patterns in memristor synapse-coupled Hopfield neural network with two neurons
• Hidden dynamics in a fractional-order memristive Hindmarsh-Rose model
• Hidden multistability in a memristor-based cellular neural network
• On hyperchaos in a small memristive neural network
• Design and realization of discrete memristive hyperchaotic map with application in image encryption
• A simple locally active memristor and its application in HR neurons
• Chaos in a Simplest Cyclic Memristive Neural Network
• Dynamic behaviors of hyperbolic-type memristor-based Hopfield neural network considering synaptic crosstalk
• Neurons with graded response have collective computational properties like those of two-state neurons.
• Hidden extreme multistability with hyperchaos and transient chaos in a Hopfield neural network affected by electromagnetic radiation
• Complex dynamics in a Hopfield neural network under electromagnetic induction and electromagnetic radiation
• Resonance and bifurcation of fractional quintic Mathieu-Duffing system

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