Design and learning with cellular neural networks

Abstract

The template coefficients (weights) of a CNN, which will give a desired performance, can either be found by design or by learning; "By design" means, that the desired function to be performed could be translated into a set of local dynamic rules, while "by learning" is based exclusively on pairs of input and corresponding output signals, the relationship of which may be by far too complicated for the explicit formulation of local rules. An overview of design and learning methods applicable to CNNs, which sometimes are not clearly distinguishable,is given here. Both technological constraints imposed by specific hardware implementation and practical constraints caused by the specific application and system embedding are influencing design and learning.<>