Three-Output Cellular Neural Network and Its Application to Diagnosing Liver Diseases.
Zhong Zhang, Hiroaki Kawabata, 道弘 難波 · TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C · 2001
It is well known that cellular neural network (CNN) is very effective as an associative memory medium. And the saturation (output) function plays an important role in CNN, because it affects the operation, the stable equilibrium points and the performance of CNN. However, to the best of our knowledge a systematic design procedure for the output function is not available in the literature. In this paper, we present a simple, yet, effective design method for the three-output cellular neural network (TCNN). To demonstrate the effectiveness of the output function, we tested TCNN on synthesized images. In addition, we applied TCNN to diagnosing liver diseases and obtained very encouraging results.