Implementing dynamic reconfigurable CNN-based full-adder

This paper presents a new approach to implement the dynamic reconfigurable logical systems based on Cellular Neural Networks (CNN), comparing with utilizing the chaos computing system, which is easier to implement in engineering applications and more stable. We provided and experimentally demonstrated the basic principle for obtaining a full-adder by using uncoupled CNN cells. The actual circuit to implementing the full-adder and transforming from adder to subtractor also has been presented.