Noise and synchronization in chaotic neural networks

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)22_Publication in policy or professional journal

20 Scopus Citations
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Author(s)

  • J. W. Shuai
  • K. W. Wong

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)7002-7007
Journal / PublicationPhysical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
Volume57
Issue number6
Publication statusPublished - Jun 1998

Abstract

We show that two identical fully connected chaotic neural networks can always achieve a stochastic synchronization state when linked with a sufficiently large common noise. This is the case for both low-dimensional hyperchaos and high-dimensional spatiotemporal chaos. When the parameters of the two driven systems possess a tiny difference, weakly noise-induced synchronization is obtained. Unstable finite-precision synchronization of chaos with positive conditional Lyapunov exponent is also observed. It is caused by the on-off synchronizing intermittent dynamics.