DocumentCode :
768055
Title :
Holographic reduced representations
Author :
Plate, Tony A.
Author_Institution :
British Columbia Cancer Res. Centre, Vancouver, BC, Canada
Volume :
6
Issue :
3
fYear :
1995
fDate :
5/1/1995 12:00:00 AM
Firstpage :
623
Lastpage :
641
Abstract :
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
Keywords :
associative processing; content-addressable storage; convolution; holographic storage; neural nets; associative memory; circular convolution; compositional structures; holographic reduced representations; neural nets; vectors; Artificial intelligence; Associative memory; Cancer; Concrete; Convolution; Councils; Degradation; Holography; Tree data structures;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/72.377968
Filename :
377968
Link To Document :
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