主动站点模型的Delta学习规则
Delta Learning Rule for the Active Sites Model
摘要：
本文报道了利用Widrow-Hoff学习规则比较实现B矩阵方法的Hebbian神经网络的记忆提取能力的方法的结果。然后，我们扩展了最近提出的活动站点模型，通过开发一个增量规则来增加内存容量。同时，本文将二进制神经网络推广到多层（非二进制）神经网络。
英文摘要：
This paper reports the results on methods of comparing the memory retrieval capacity of the Hebbian neural network which implements the B-Matrix approach, by using the Widrow-Hoff rule of learning. We then, extend the recently proposed Active Sites model by developing a delta rule to increase memory capacity. Also, this paper extends the binary neural network to a multi-level (non-binary) neural network.
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。
