Efficient learning algorithm for Fuzzy bi-directional associative memory based on Lukasiewicz''''s t-Norm
基于Lukasiewicz t-模的模糊双向联想记忆网络的有效学习算法

Taking advantage of the concomitant implication operator of T_ L , which is a t-norm, a simple efficient learning algorithm was proposed for the fuzzy bi-directional associative memory based on fuzzy composition of Max and T_ L (Max-T_ L FBAM). It is proved theoretically that, if there is a connected weight matrix which make arbitrarily given pattern pairs set become stability state set of Max-T_ L FBAM, then the proposed learning algorithm can find the maximum of all connected weight matrices . An experiment was given to test the effectiveness of the presented learning algorithm.