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<p>The coupled neurons of a Hopfield neural network (HNN) is create electromagnetic induction flows in response to variations in membrane potential. The computational efficiency of their network is significantly influenced by the coupling between neural oscillators. This study proposes a unified memristive HNN model that coupled neurons with nonlinear coupling utilizing hyperbolic-type memristors to describe the induction fluxes. Studying the neuronal spatiotemporal patterns is one of the most effective techniques for dealing with the high-level complexity that is being investigated. In the proposed model, we have examined the impact of an external force’s frequency and amplitude on the spiral wave’s dynamics throughout a neural network. The simulation of neuronal synchronization and aberrant signal transmission at the molecular level is made possible through the wave propagation, which contributes to the recognizing of brain illnesses.</p>

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Analysis of spiral wave in a Hopfield neural network under electromagnetic induction and control with external magnetic flux

  • 期刊论文

  • 发表日期：

    2025年6月10日

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  • Sajal Debnath,
  • Santimoy Kundu

摘要

The coupled neurons of a Hopfield neural network (HNN) is create electromagnetic induction flows in response to variations in membrane potential. The computational efficiency of their network is significantly influenced by the coupling between neural oscillators. This study proposes a unified memristive HNN model that coupled neurons with nonlinear coupling utilizing hyperbolic-type memristors to describe the induction fluxes. Studying the neuronal spatiotemporal patterns is one of the most effective techniques for dealing with the high-level complexity that is being investigated. In the proposed model, we have examined the impact of an external force’s frequency and amplitude on the spiral wave’s dynamics throughout a neural network. The simulation of neuronal synchronization and aberrant signal transmission at the molecular level is made possible through the wave propagation, which contributes to the recognizing of brain illnesses.