Cellular Neural Networks and Its Application for Abnormal Detection
Zhong Zhang, Michihiro Namba, Hiroaki Kawabata, Akihiro Kanagawa · Transactions of the Society of Instrument and Control Engineers · 2003
It is well known that the 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 two and three-output functions. To demonstrate the effectiveness of the output functions, we tested CNN on synthesized images. In addition, we applied CNN to recongnize Chinese characteres and diagnose liver diseases, and obtained very encouraging results.