CNN-like networks based on multi-valued and universal binary neurons: learning and application to image processing
Naum N. Aizenberg, Igor N. Aizenberg · 2002
We consider fast convergence learning algorithms for multi-valued and universal binary neurons. These neurons are suggested to be used for design of neural networks based on CNN paradigm. On the basis of such networks we offer to solve some problems of image processing. For instance, high efficient method for contours detection obtained by learning algorithm described in the paper is presented. Also solution of the XOR-problem on the single neuron is described.>