Plate T A
British Columbia Cancer Res. Centre, Vancouver, BC.
IEEE Trans Neural Netw. 1995;6(3):623-41. doi: 10.1109/72.377968.
Associative memories are conventionally used to represent data with very simple structure: sets of pairs of vectors. This paper describes a method for representing more complex compositional structure in distributed representations. The method uses circular convolution to associate items, which are represented by vectors. Arbitrary variable bindings, short sequences of various lengths, simple frame-like structures, and reduced representations can be represented in a fixed width vector. These representations are items in their own right and can be used in constructing compositional structures. The noisy reconstructions extracted from convolution memories can be cleaned up by using a separate associative memory that has good reconstructive properties.
向量对的集合。本文描述了一种在分布式表示中表示更复杂组合结构的方法。该方法使用循环卷积来关联由向量表示的项。任意变量绑定、各种长度的短序列、简单的框架状结构以及简化表示都可以用固定宽度的向量来表示。这些表示本身就是项,可用于构建组合结构。从卷积记忆中提取的有噪声的重建可以通过使用具有良好重建特性的单独关联记忆来清理。