Image processing using cellular neural networks based on multi-valued and universal binary neurons
I. Aizenberg, N. Aizenberg, T. Bregin, Constantine Butakoff, Elya Farberov · 2002
Multi-valued neurons (MVNs) and universal binary neurons (UBNs) are neural processing elements with complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by a partially-defined multiple-valued function on a single MVN, and an arbitrary mapping described by a partially-defined or fully-defined Boolean function (which does not have to be a threshold function) on a single UBN. Rapidly-converging learning algorithms exist for both types of neurons. Such features of MVNs and UBNs may be used to solve different kinds of problems. One of the most successful applications of MVNs and UBNs is their use as basic neurons in cellular neural networks (CNNs) to solve image processing and image analysis problems.