Title

Properties Of Learning Related To Pattern Diversity In Art1

Title - Alternative

Neural Netw.

Abstract

In this paper we consider a special class of the ART1 neural network. It is shown that if this network is repeatedly presented with an arbitrary list of binary input patterns, learning self-stabilizes in at most m list presentations, where m corresponds to the number of patterns of distinct size in the input list. Other useful properties of the ART1 network, associated with the learning of an arbitrary list of binary input patterns, are also examined. These properties reveal some of the "good" characteristics of the ART1 network when it is used as a tool for the learning of recognition categories.

Publication Title

Neural Networks

Volume

4

Issue/Number

6

Publication Date

1-1-1991

Document Type

Article

Language

English

First Page

751

Last Page

757

WOS Identifier

WOS:A1991GW46500005

ISSN

0893-6080

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