Hopfield网络中的逻辑学习
Logic Learning in Hopfield Networks
摘要：
在逻辑编程中，神经元的突触权重可以通过使用Hebbian学习或Wan Abdullah的方法来计算。换句话说，对于对应于一些相应程序子句的支配事件的赫布学习等价于对于相同的相应程序子句使用万阿卜杜拉方法的学习。在本文中，我们将通过计算机模拟实验评估这两种类型的学习之间的等效性。
英文摘要：
Synaptic weights for neurons in logic programming can be calculated either by using Hebbian learning or by Wan Abdullah's method. In other words, Hebbian learning for governing events corresponding to some respective program clauses is equivalent with learning using Wan Abdullah's method for the same respective program clauses. In this paper we will evaluate experimentally the equivalence between these two types of learning through computer simulations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
