Cellular neural networks: Mosaic patterns, bifurcation and complexity

Juang Jonq*, L. I. Chin-Lung, Ming Huang Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

We study a one-dimensional Cellular Neural Network with an output function which is nonflat at infinity. Spatial chaotic regions are completely characterized. Moreover, each of their exact corresponding entropy is obtained via the method of transition matrices. We also study the bifurcation phenomenon of mosaic patterns with bifurcation parameters z and β. Here z is a source (or bias) term and β is the interaction weight between the neighboring cells. In particular, we find that by injecting the source term, i.e. z ≠ 0, a lot of new chaotic patterns emerge with a smaller interaction weight β. However, as β increases to a certain range, most of previously observed chaotic patterns disappear, while other new chaotic patterns emerge.

Original languageEnglish
Pages (from-to)47-57
Number of pages11
JournalInternational Journal of Bifurcation and Chaos
Volume16
Issue number1
DOIs
StatePublished - 1 Jan 2006

Keywords

  • Bifurcation
  • Cellular neural networks
  • Mosaic patterns
  • Spatial entropy
  • Transition matrix

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