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The N-N-N conjecture in ART1

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3 Author(s)
Georgiopoulos, M. ; Dept. of Electr. Eng., Univ. of Central Florida, FL, USA ; Heileman, G.L. ; Huang, J.

The authors consider the ART1 neural network architecture introduced by G.A. Carpenter and S. Grossberg (Comput. Vis., Graph., and Image Process. vol.37, 54-115, 1987). In their original paper, Carpenter and Grossberg made the following conjecture. In the fast learning case if the F2 layer in ART1 has at least N nodes, then each member of a list of N input patterns presented cyclically at the F1 layer of ART1 will have direct access to an F2 layer nodes after at most N list representations. It is demonstrated that the conjecture is not valid for certain large L values, where L is a network parameter associated with the adaptation of the bottom-traces in ART1. It is noted that previous work has shown the conjecture to be true for small L values

Published in:

Neural Networks, 1992. IJCNN., International Joint Conference on  (Volume:4 )

Date of Conference:

7-11 Jun 1992