Applications and Oscillatory Phenomena of Cellular Neural Network Using Two Kinds of Cloning Templates

Abstract

In this paper, a cellular neural network using two kinds of cloning templates, which is a kind of modified cellular neural networks (CNN), is proposed and investigated. The structure of this system is almost the same as that of the conventional CNN. Namely, the only difference between the conventional CNN and the proposed system is the number of signal lines used for cloning templates. Therefore, the difficulty of IC implementation is almost the same. This system can carry out more complicated processing than the conventional CNN. Additionally, cloning templates of the conventional CNN can be applied to this system. As applications, five different cloning templates for image processing that can carry out complicated processing and a demonstration of an image-processing application are shown. In the demonstration, by using two cloning templates for the proposed system and three cloning templates for the conventional CNN, we demonstrate the extraction of numbers drawn with a hard-to-distinguish color in the background of postage stamps. On the other hand, oscillatory phenomena can be observed in the case of a periodic boundary condition and a symmetry-cloning template. In the case of the conventional CNN with a corresponding condition, oscillatory phenomena cannot be observed. The proposed system consists of two kinds of cells that cannot oscillate on their own. Namely, elements of the oscillator are shared among each other. In this point, the proposed system is of interest. Synchronization, quasi-synchronization and clustering phenomena are observed in the proposed system. The system is analyzed and the oscillation of the system is verified.