doi: 10.18178/ijfcc.2015.4.5.411
Dynamic Analysis of Coupled Binary Cow Patch Cellular Neural Networks
Min Li
,
Lequan Min
,
Mian Wang
- School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, PR China.
Abstract
Nature abounds with complex patterns emergingfrom biological, chemical, physical and social systems. CellularNeural Networks (CNNs) may produce patterns similar to thosefound in nature, which implies that CNNs may be used asprototypes to describe some systems in nature. The Cow PatchCNNs introduced by Chua et al. can generate pattern that cowpatches and checkerboards coexist from any random initialpattern. In order to investigate the characteristics of the BinaryCow Patch CNNs, this study introduces concepts of so-calledinherent (final) active, inherent (final) passive, and inherent(final) neutral for pattern pixels, and proposes Global Task andLocal Rules of the Binary Cow Patch CNNs, and establishes aset of theorems. Three simulation examples have been carriedout to verify the effectiveness of theoretical results.
Keywords
- Binary cow patch CNN
- initial state
- binaryimage
- global task
- local rules
How to Cite
Min Li, Lequan Min, and Mian Wang, "Dynamic Analysis of Coupled Binary Cow Patch Cellular Neural Networks," International Journal of Future Computer and Communication, vol. 4, no. 5, pp. 328-335, 2015. https://doi.org/ 10.18178/ijfcc.2015.4.5.411
Copyright & License
Copyright © 2015 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).