Chaos in nhterogeneous networks with temporally inert nodes

J. J. Torres, J. Marro, S. De Franciscis

Research output: Contribution to journalArticlepeer-review


We discuss an attractor neural network in which only a fraction ρ of nodes is simultaneously updated. In addition, the network has a heterogeneous distribution of connection weights and, depending on the current degree of order, connections are changed at random by a factor Φ on short-time scales. The resulting dynamic attractors may become unstable in a certain range of Φ thus ensuing chaotic itineracy which highly depends on ρ. For intermediate values of ρ, we observe that the number of attractors visited increases with ρ, and that the trajectory may change from regular to chaotic and vice versa as ρ is modified. Statistical analysis of time series shows a power-law spectra under conditions in which the attractors' space is most efficiently explored.

Original languageEnglish
Pages (from-to)677-686
Number of pages10
JournalInternational Journal of Bifurcation and Chaos
Issue number2
Publication statusPublished - 2009


  • Chaotic switching
  • Complex functionality in networks
  • Criticality
  • Transition to chaos

ASJC Scopus subject areas

  • Applied Mathematics
  • General
  • Engineering(all)
  • Modelling and Simulation


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