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Tri-output cellular neural network and its application to diagnosing liver diseases

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3 Author(s)
Zhong Zhang ; Dept. of Syst. Eng., Ind. Technol. Center of Okayama Prefecture, Japan ; Zhi-Qiang Liu ; H. Kawabata

The saturation (output) function is important to cellular neural networks (CNN) because it affects the operation, 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 tri-output cellular neural network (TCNN). To demonstrate the effectiveness of the output function using our design procedure, we tested TCNN on synthesized images. In addition, we applied the tri-output cellular neural network to the diagnosis of liver diseases and obtained very encouraging results

Published in:

Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on  (Volume:3 )

Date of Conference:

1999