Time-Delay ART for spatio-temporal patterns

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4 Citations (Scopus)

Abstract

This paper proposes a new self-organizing neural network for spatio-temporal patterns called Time-Delay ART (TD-ART). The TD-ART is a nearest neighbor classifier that stores arbitrary length of spatio-temporal patterns. It has at least three layers. The Layer-1 and the Layer-2 classify input spatial patterns one by one: the algorithm is based on the Carpenter/Grossberg net algorithm. The Layer-2 and the Layer-3 classify and memorize the sequence of the spatial patterns classified in the Layer-2. The connections between the Layer-2 and the Layer-3 are adjusted both in weight and in time-delay to deal with spatio-temporal patterns. Although the construction and operation of TD-ART are very simple, it has many features such as its self-organization, classification, and memorization abilities for spatio-temporal patterns. In addition, the TD-ART can distinguish different sequences composed of same patterns such as A → C → T and C → A → T by unsupervised learning, and can deal with many sequences of different lengths.

Original languageEnglish
Pages (from-to)513-521
Number of pages9
JournalNeurocomputing
Volume6
Issue number5-6
DOIs
Publication statusPublished - 1994 Oct

Keywords

  • ART
  • Associative memory
  • Spatio-temporal pattern
  • Time-delay
  • Unsupervised learning

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

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