On the templates corresponding to cycle-symmetric connectivity in cellular neural networks

Chih-Wen Shih*, Chih-Wen Weng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

In the architecture of cellular neural networks (CNN), connections among cells are built on linear coupling laws. These laws are characterized by the so-called templates which express the local interaction weights among cells. Recently, the complete stability for CNN has been extended from symmetric connections to cycle-symmetric connections. In this presentation, we investigate a class of two-dimensional space-invariant templates. We find necessary and sufficient conditions for the class of templates to have cycle-symmetric connections. Complete stability for CNN with several interesting templates is thus concluded.

Original languageEnglish
Pages (from-to)2957-2966
Number of pages10
JournalInternational Journal of Bifurcation and Chaos in Applied Sciences and Engineering
Volume12
Issue number12
DOIs
StatePublished - Dec 2002

Keywords

  • Complete stability
  • Cycle-symmetric matrix
  • Neural network

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