On the separating capability of cellular neural networks

The cellular neural network is able to perform different image-processing tasks depending on the template values, i.e. the network parameters, used. In the case of linear templates the parameter space is divided into different regions by hyperplanes. Every region is associated with a task, such that all points within that region let the cellular neural network perform the desired task. In this paper a lower and an upper bound for the number of regions that can be separated with binary-input cellular neural networks are given, thus answering the question of how many different-tasks such a cellular neural network can perform.