Transient dynamics for sequence processing neural networks: effect of degree distributions

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dc.creatorChen, Yong
dc.creatorZhang, Pan
dc.creatorYu, Lianchun
dc.creatorZhang, Shengli
dc.date2007-05-24
dc.date2008-01-31
dc.date.accessioned2026-07-07T08:57:12Z
dc.date.available2026-07-07T08:57:12Z
dc.descriptionWe derive a analytic evolution equation for overlap parameters including the effect of degree distribution on the transient dynamics of sequence processing neural networks. In the special case of globally coupled networks, the precisely retrieved critical loading ratio $α_c = N ^{-1/2}$ is obtained, where $N$ is the network size. In the presence of random networks, our theoretical predictions agree quantitatively with the numerical experiments for delta, binomial, and power-law degree distributions.
dc.description11 pages, 6 figures
dc.identifierhttps://arxiv.org/abs/0705.3679
dc.identifierhttp://arxiv.org/abs/0705.3679
dc.identifierPhys. Rev. E 77, 016110 (2008)
dc.identifierdoi:10.1103/PhysRevE.77.016110
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/146874
dc.subjectDisordered Systems and Neural Networks
dc.subjectStatistical Mechanics
dc.titleTransient dynamics for sequence processing neural networks: effect of degree distributions
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