Distributed Patterns as Hierarchical Structures
نویسندگان
چکیده
Recursive Auto-Associative Memory (RAAM) structures show promise as a general representation vehicle that uses distributed patterns. However training is often difficult, which explains, at least in part, why only relatively small networks have been studied. We show a technique for transforming any collection of hierarchical structures into a set of training patterns for a sequential RAAM which can be effectively trained using a simple (Elman-style) recurrent network. Tr aining produces a set of distributed patterns corresponding to the structures.
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