Design technique of cellular neural network
Koji Nakai, Akio Ushida · Electronics and Communications in Japan (Part III Fundamental Electronic Science) · 1995
Abstract The cellular neural network (CNN) is composed of a planar placement of cells which consists of a (piecewise‐linear) nonlinear element and controlled current sources. It features a simple structure which is close to that of the retina and is expected to be utilized in pattern recognition and image processing. In CNN, each cell is connected to the neighborhood cells by the same pattern, and by adjusting the connection pattern, CNN with various functions can be designed. the connection pattern is called the cloning template. It is very important in the development of new CNN to establish the design method for the cloning template. In this paper, the operational characteristics are assumed so that the output for the normative input satisfies the specified conditions. the constraint is derived from the specification and the template is designed so that the corresponding cost function is minimized. the simplex method is used as the optimization technique, which features a simple algorithm. As application examples, noise‐remover CNN as well as the maze‐tracing CNN are designed and satisfactory results are obtained. the design method is reported in this paper.