Hetero-association for pattern translation
Francis T. S. Yu, Thomas T. Lu, Xiangyang Yang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1991
A hetero-association neural network using an interpattern association algorithm is presented. By using simple logical rules, hetero-association memory can be constructed based on the association between the input-output reference patterns. For optical implementation, a compact size liquid crystal television neural network is used. Translations between the English letters and the Chinese characters as well as Arabic and Chinese numerics are demonstrated. The authors have shown that the hetero-association model can perform more effectively in comparison to the Hopfield model in retrieving large numbers of similar patterns.