Generalized CNN: Potentials of a CNN with non-uniform weights

A generalization of the cellular neural network (CNN) paradigm is obtained by removing the uniformly constraint on weight values. Such generalized CNNs are capable of new tasks, such as function approximation or associative memory. A stability analysis of these networks is presented. Adaptation and application of a gradient descent learning algorithm is then discussed