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A Cu-Doped TiO<sub>2-</sub> <i> <sub>x</sub> </i> Nanoscale Memristor With Application to Heterogeneous Coupled Neurons

Yuan Fang, Xiangcheng Yu, Yue Deng, Yuxia Li, Guanrong Chen

2023IEEE Transactions on Industrial Electronics26 citationsDOI

Abstract

This article introduces Cu-doped TiO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2-</sub> <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><sub>x</sub></i> nanoscale memristors into a heterogeneous coupled neuronal system constructed by two-dimensional Hindmarsh–Rose and Fitzhugh–Nagumo neurons to simulate electromagnetic induction. The proposed memristive coupled neurons can generate various firing activities, including periodic spiking firing pattern, transient chaos pattern, double chaotic firing pattern, and some other complex firing patterns. In addition, the phase synchronization of coupled neurons is analyzed based on the coupling strength. Finally, an experimental circuit is built to explore the effect of physical memristors on neuronal firing activities, which confirms the correctness of the theoretical analysis.

Topics & Concepts

MemristorSynchronization (alternating current)CorrectnessChaoticCoupling (piping)Topology (electrical circuits)DopingPhysicsBiological systemPhase (matter)Nanoscopic scaleComputer scienceMaterials scienceElectronic engineeringOptoelectronicsNanotechnologyAlgorithmElectrical engineeringArtificial intelligenceEngineeringQuantum mechanicsBiologyMetallurgyAdvanced Memory and Neural Computingstochastic dynamics and bifurcationNeural dynamics and brain function
A Cu-Doped TiO<sub>2-</sub> <i> <sub>x</sub> </i> Nanoscale Memristor With Application to Heterogeneous Coupled Neurons | Litcius