The N-N-N Conjecture in ART1

M. Georgiopoulos, G. L. Heileman, J. Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this paper we consider the ART1 neural network architecture introduced by Carpenter and Grossberg. In their original paper, Carpenter and Grossberg made the following conjecture: In the fast learning case, if the F2layer in ART1 has at least N nodes, then each member of a list of N input patterns presented cyclically at the F1layer of ART1 will have direct access to an F2layer node after at most N list presentations. In this paper, we demonstrate that the conjecture is not valid for certain large L values, where L is a network parameter associated with the adaptation of the bottom-up traces in ART1. It is worth noting that previous work has shown the conjecture to be true for small L values.

Original languageEnglish (US)
Title of host publicationProceedings - 1992 International Joint Conference on Neural Networks, IJCNN 1992
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)0780305590
StatePublished - 1992
Externally publishedYes
Event1992 International Joint Conference on Neural Networks, IJCNN 1992 - Baltimore, United States
Duration: Jun 7 1992Jun 11 1992

Publication series

NameProceedings of the International Joint Conference on Neural Networks


Conference1992 International Joint Conference on Neural Networks, IJCNN 1992
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence


Dive into the research topics of 'The N-N-N Conjecture in ART1'. Together they form a unique fingerprint.

Cite this