A net-structure learning system for pattern description

This paper discusses a computer program that recognizes and describes two-dimensional patterns composed of subpatterns. The program also recognizes all patterns in a scene consisting of several patterns.

Patterns are stored in a learned hierarchical, net-structure memory. Weighted links between memory nodes represent subpattern/pattern relationships. Both short term and permanent memories are used.

Pattern recognition is accomplished with a serial heuristic search algorithm, which attempts to search memory and compute input properties efficiently. Without special processing, the program can be asked to look for all occurrences of a specified pattern in a scene.