Effects of network topologies on stochastic resonance in feedforward neural network.
Degree distribution
Feedforward network
Stochastic resonance
Topology
Journal
Cognitive neurodynamics
ISSN: 1871-4080
Titre abrégé: Cogn Neurodyn
Pays: Netherlands
ID NLM: 101306907
Informations de publication
Date de publication:
Jun 2020
Jun 2020
Historique:
received:
09
09
2019
revised:
26
01
2020
accepted:
05
03
2020
entrez:
14
5
2020
pubmed:
14
5
2020
medline:
14
5
2020
Statut:
ppublish
Résumé
The effects of network topologies on signal propagation are studied in noisy feedforward neural network in detail, where the network topologies are modulated by changing both the in-degree and out-degree distributions of FFNs as identical, uniform and exponential respectively. Stochastic resonance appeared in three FFNs when the same external stimuli and noise are applied to the three different network topologies. It is found that optimal noise intensity decreases with the increase of network's layer index. Meanwhile, the
Identifiants
pubmed: 32399079
doi: 10.1007/s11571-020-09576-8
pii: 9576
pmc: PMC7203268
doi:
Types de publication
Journal Article
Langues
eng
Pagination
399-409Informations de copyright
© Springer Nature B.V. 2020.
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