An Efficient Learning Algorith for Associative Memory Neural Network
联想记忆神经网络的一个有效学习算法

A new and efficient learning algorithm of asociative memory neural network is proposed,with the following characteristics:(1)it can store any given training pattern set no matter how much and what correlation among them may be;(2)the smallest domain of attraction of training patterns is maximized;(3)each domain of attraction of training patterns is guaranteed to be as large as possible;(4)the designed associative memory network is globally stable.A large number of computer experimental results confirm that our algorithm possesses more powerful storage ability and more fault tolerance capability than existing ones.