Kawamura M, Okada M, Hirai Y
Doctoral Program in Engineering, University of Tsukuba, Tsukuba-shi, 305-8573, Japan.
IEEE Trans Neural Netw. 1999;10(3):704-13. doi: 10.1109/72.761729.
The dynamics of selective recall in an associative memory model are analyzed in the scenario of one-to-many association. One-to-many association is one of the most important characteristics of our memory system because a homophone, for example, associates with more than one word and each word can have several meanings. The present model, which can deal with one-to-many association, consists of a heteroassociative network and an autoassociative network. In the heteroassociative network, a mixture of associative items in one-to-many association is recalled by a key item. In the autoassociative network, the selective recall of one of the associative items is examined by providing a seed of a target item either to the heteroassociative network (Model 1) or to the autoassociative network (Model 2). We show by both simulation studies and theoretical analysis that the critical similarity of Model 2 is not sensitive to the change in the dimension ratio of key vectors to associative vectors, and it has smaller critical similarity (correlation between the seed and the target item) than Model 1 for a large initial overlap. On the other hand, we show that Model 1 has smaller critical similarity for a small initial overlap. We also show that unreachable equilibrium states exist in the proposed model. There is a critical loading rate alphar where the reachable equilibrium states are disappeared. Above the critical loading rate alphar, which is smaller than the storage capacity alphac, all equilibrium states are stable, but cannot be reached.
在一对多关联的情境下，分析了关联记忆模型中的选择性回忆动态。一对多关联是我们记忆系统最重要的特征之一，例如，一个同音异义词与多个单词相关联，且每个单词可能有多种含义。当前这个能够处理一对多关联的模型，由一个异质关联网络和一个自关联网络组成。在异质关联网络中，通过一个关键项来回忆一对多关联中的关联项混合体。在自关联网络中，通过向异质关联网络（模型1）或自关联网络（模型2）提供目标项的一个种子，来检验其中一个关联项的选择性回忆。我们通过模拟研究和理论分析表明，模型2的临界相似度对关键向量与关联向量的维度比变化不敏感，并且对于较大的初始重叠，它比模型1具有更小的临界相似度（种子与目标项之间的相关性）。另一方面，我们表明对于较小的初始重叠，模型1具有更小的临界相似度。我们还表明在所提出的模型中存在不可达的平衡态。存在一个临界负载率αr，在该负载率下可达平衡态消失。高于临界负载率αr（αr小于存储容量αc）时，所有平衡态都是稳定的，但无法达到。
