Discrete‐time cellular neural networks

摘要

AbstractA network structure called a discrete‐time cellular neural network is introduced. It is derived from cellular neural networks and feedback threshold networks. the architecture is discussed and its advantages are presented. Convergence is proved for a large class of templates and applications are given for the following image‐processing tasks: linear thresholding, connected component detection, hole filling, concentric contouring, increasing and decreasing objects step by step, searching for objects with minimal distance, and oscillat