A DT-CNN data-flow implementation

Digital implementations of Cellular Neural Networks are studied in terms of their communication requirements. Secure and reliable communication seems to imply close control, which degrades performance. We introduce a mechanism that removes the need for explicit local network control, taking the internal network communication out of the performance equation. This allows handling boundary conditions without introducing additional cells and facilitates multi-level implementations. A typical feature extraction task in hand vein recognition shows a 20times performance improvement for the Cellular Neural Network implementation.