Multidirectional Associative Memory Neural Network Circuit Based on Memristor

Du, Sichun; Zhang, Zedi; Li, Jun; Sun, Chen; Sun, Jingru; Hong, Qinghui

doi:10.1109/tbcas.2023.3276077

Cited by 9 publications

(1 citation statement)

References 49 publications

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“…Memristor has remarkable bionic properties such as plasticity, memorability, nonlinearity and nanometer size, and can therefore be taken to mimic biological synapse for reproducing the electrical activity in neurons [26][27][28][29][30][31]. Ding investigated the discharge dynamics of fractionalorder memristor-coupled HR neurons considering synaptic crosstalk [32].…”

Section: Introductionmentioning

confidence: 99%

Electrical activity and synchronization of HR-tabu neuron network coupled by Chua corsage memristor

Li,

Wang,

et al. 2023

Preprint

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The processing and transmission of biological neural information are jointly completed by the electromagnetic activities of neurons in different brain regions. Therefore, it’s of great significance to explore the electrical behavior of heterogeneous neuron network. This paper focuses on the electrical activity and synchronization of a bi-neuron network (HR-tabu neuron network) built by coupling Hindmarsh-Rose and tabu learning models with Chua corsage memristor (CCM). The electrical activities of HR-tabu network, such as spiking discharge and bursting discharge, are revealed under appropriate external stimuli and coupling strength. Interestingly, we find that the initial value-related state switching of HR-tabu network is associated with the equilibrium states of CCM. In addition, the synchronization behavior of HR-tabu network depending on the coupling strength, external stimuli and system parameters is investigated in detail by analyzing the phase difference and synchronization factor. It’s shown that phase synchronization of HR-tabu neuron network can be achieved under small coupling strength, and that complete synchronization can be achieved when the coupling strength is large enough.

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