Can distributed delays perfectly stabilize dynamical networks?

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dc.creatorOmi, Takahiro
dc.creatorShinomoto, Shigeru
dc.date2007-10-18
dc.date.accessioned2026-07-07T09:33:03Z
dc.date.available2026-07-07T09:33:03Z
dc.descriptionSignal transmission delays tend to destabilize dynamical networks leading to oscillation, but their dispersion contributes oppositely toward stabilization. We analyze an integro-differential equation that describes the collective dynamics of a neural network with distributed signal delays. With the gamma distributed delays less dispersed than exponential distribution, the system exhibits reentrant phenomena, in which the stability is once lost but then recovered as the mean delay is increased. With delays dispersed more highly than exponential, the system never destabilizes.
dc.description4pages 5figures
dc.identifierhttps://arxiv.org/abs/0710.3475
dc.identifierhttp://arxiv.org/abs/0710.3475
dc.identifierPHYSICAL REVIEW E 77, 046214 (2008)
dc.identifierdoi:10.1103/PhysRevE.77.046214
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/159001
dc.subjectDisordered Systems and Neural Networks
dc.subjectAdaptation and Self-Organizing Systems
dc.titleCan distributed delays perfectly stabilize dynamical networks?
dc.typetext

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