THE MOSAIC PATTERNS OF CNN WITH SYMMETRIC FEEDBACK TEMPLATE

Abstract

In this paper, the mosaic patterns of the two-dimensional cellular neural network (CNN) with symmetric feedback template are investigated. For our CNN system, the parameter space is constructed by the output synaptic weights and the threshold, and it is partitioned into finitely many regions through geometric methods and variable substitution. Fixing the output synaptic weights and the threshold in some regions, we give the necessary and sufficient conditions to all mosaic patterns of the CNN systems.