Title

A Survey Of Learning Results In Art Architectures

Keywords

ART; Learning; Neural networks; Performance; Training

Abstract

In this paper we investigate, in unison, the learning properties of ART1, Fuzzy ART and ARTMAP architectures. These architectures were introduced by Carpenter and Grossberg over a time period spanning the last eight years. Some of the learning properties discussed in this paper involve characteristics of the clusters formed in these architectures, while other learning properties concentrate on how fast it will take these architectures to converge to a solution for the type of problems that are capable of solving. This latter issue is a very important issue in the neural network literature, and there are very few instances where it has been answered satisfactorily.

Publication Date

4-6-1995

Publication Title

Proceedings of SPIE - The International Society for Optical Engineering

Volume

2492

Number of Pages

416-424

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1117/12.205147

Socpus ID

85079809025 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85079809025

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