Classification of Dynamics for 1X2 Cellular Neural Networks

• Main Authors: Chiao-Ju Li, 李喬如
• Other Authors: Chih-Wen Shih
• Format: Others
• Language: en_US
• Published: 1999
• Online Access: http://ndltd.ncl.edu.tw/handle/09888209365995646283

碩士 === 國立交通大學 === 應用數學系 === 87 === This presentation investigates the dynamics of a 1X2 cellular neural network. As CNN is dissipative, it possesses a global attractor. In addition, it has been shown in a previous literature that CNN with symmetric template and with finitely many cells is completely stable. Under this circumstance, the global attractor contains only equilibria and the unstable manifolds of the equilibria. The connecting orbits between equilibria lie on these unstable manifolds. Therefore, for 1X2 cellular neural network with symmetric template, the dynamics are determined through characterizing the connecting orbits between equilibria. In this investigation, all the connecting orbits between equilibria can be classified, for regular parameters. Vector field analysis as well as numerical experiments are also performed to obtain the configurations and the locations of these connecting orbits. This study hopes to stir up further inspiration in the studies of dynamics for CNN.