COMPARISON OF SYNCHRONIZATION SPEED OF RING NETWORKS OF REACTION-DIFFUSION EQUATIONS OF FITZHUGH-NAGUMO TYPE WITH UNIDIRECTIONAL AND BIDIRECTIONAL COUPLING

The purpose of this work is to research the numerical results of the comparison of the synchronization speed of ring neural networks with unidirectional and bidirectional coupling. Each neuron is linearly coupled with the others and represented by a system of reaction-diffusion equations of the FitzHugh-Nagumo type. The result shows that the necessary coupling strength for the synchronization in two cases increases when the number of neurons increases. In other words, the greater the number of neurons in the ring networks is, the more difficult the synchronization occurs. Moreover, synchronizing the ring networks with bidirectional coupling is easier than the one with unidirectional coupling over the same given number of neurons.

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Publication Details

Journal
Advanced mathematical models & applications.
Published
2024-12-04
DOI
https://doi.org/10.62476/amma93401
Primary Topic
Neural Networks and Applications
Type
article
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article

COMPARISON OF SYNCHRONIZATION SPEED OF RING NETWORKS OF REACTION-DIFFUSION EQUATIONS OF FITZHUGH-NAGUMO TYPE WITH UNIDIRECTIONAL AND BIDIRECTIONAL COUPLING

Phan Van Long Em
Advanced mathematical models & applications.
Neural Networks and Applications
article

COMPARISON OF SYNCHRONIZATION SPEED OF RING NETWORKS OF REACTION-DIFFUSION EQUATIONS OF FITZHUGH-NAGUMO TYPE WITH UNIDIRECTIONAL AND BIDIRECTIONAL COUPLING

Phan Van Long Em
article en

Abstract

The purpose of this work is to research the numerical results of the comparison of the synchronization speed of ring neural networks with unidirectional and bidirectional coupling. Each neuron is linearly coupled with the others and represented by a system of reaction-diffusion equations of the FitzHugh-Nagumo type. The result shows that the necessary coupling strength for the synchronization in two cases increases when the number of neurons increases. In other words, the greater the number of neurons in the ring networks is, the more difficult the synchronization occurs. Moreover, synchronizing the ring networks with bidirectional coupling is easier than the one with unidirectional coupling over the same given number of neurons.

Advanced mathematical models & applications.Vol. 9(3)
Openalex Percentile: Top 80%
Neural Networks and Applications
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