Bifurcation analysis of an oscillatory CNN model with two cells

Barnabas M. Garay, L. P. Simon

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The aim of this paper is to carry out the full bifurcation analysis of the two-parameter two-dimensional oscillatory cellular neural network (CNN) model (3)-(4) in Chap. 8 of the recent monograph of Chua and Roska (Cellular Neural Networks and Visual Computing, Cambridge University Press, [2002]). The main tool is an averaged divergence inequality implying that-regardless the dimension of the phase space-compact invariant sets are of zero Lebesgue measure.

Original languageEnglish
Pages (from-to)199-210
Number of pages12
JournalJournal of Applied Mathematics and Computing
Volume27
Issue number1-2
DOIs
Publication statusPublished - May 2008

Fingerprint

Cellular neural networks
Bifurcation Analysis
Cellular Networks
Neural Network Model
Cell
Invariant Set
Lebesgue Measure
Compact Set
Two Parameters
Phase Space
Divergence
Neural Networks
Computing
Zero
Vision

Keywords

  • Bifurcation analysis
  • Cellular neural networks
  • Liouville formula

ASJC Scopus subject areas

  • Applied Mathematics
  • Computational Mathematics

Cite this

Bifurcation analysis of an oscillatory CNN model with two cells. / Garay, Barnabas M.; Simon, L. P.

In: Journal of Applied Mathematics and Computing, Vol. 27, No. 1-2, 05.2008, p. 199-210.

Research output: Contribution to journalArticle

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