Optimizing the morphological design of discrete-time cellular neural networks

The morphological design of Discrete-Time Cellular Neural Networks (DTCNNs) has been presented in a companion paper [1]. DTCNN templates have been given for the elemental morphological operators. One way to obtain realizations for more complex operators is cascading the DTCNN equivalences of the constituent elemental operators. Here it is shown that this straightforward mapping mostly yields a non-optimal solution with respect to the required amount of hardware. A hardware reduction scheme of morphologically designed DTCNNs is proposed, which includes the introduction of time variant templates and the identification of non-elementary expressions for which a single layer DTCNN exists.