The augmented ART1 neural network

Gregory L. Heileman; Michael Georgiopoulos

The augmented ART1 neural network

Gregory L. Heileman, Michael Georgiopoulos

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A real-time neural network, AART1 (augmented adaptive resonance theory), that describes the dynamics of the ART1 model is presented. This involves modifying the architecture of the ART1 network through the addition of a reset node and a set of inhibitory nodes in the F2 layer. Along with modifications to the differential equations describing the F1 and F2 layer nodes, these changes embody the functionality of the orienting subsystem in the ART1 model. In addition, the modifications described here allow the ART1 model to be implemented solely using a set of concurrently executing nonlinear differential equations. Thus, the AART1 network requires no external control features. Computer simulation results demonstrate the efficacy of this network.

Original language	English (US)
Title of host publication	Proceedings. IJCNN - International Joint Conference on Neural Networks
Editors	Anon
Publisher	Publ by IEEE
Pages	467-472
Number of pages	6
ISBN (Print)	0780301641
State	Published - 1992
Externally published	Yes
Event	International Joint Conference on Neural Networks - IJCNN-91-Seattle - Seattle, WA, USA Duration: Jul 8 1991 → Jul 12 1991

Publication series

Name	Proceedings. IJCNN - International Joint Conference on Neural Networks

Other

Other	International Joint Conference on Neural Networks - IJCNN-91-Seattle
City	Seattle, WA, USA
Period	7/8/91 → 7/12/91

ASJC Scopus subject areas

General Engineering

Cite this

@inproceedings{b93df0ecc1bd4f24a503062f89e1ab5e,

title = "The augmented ART1 neural network",

abstract = "A real-time neural network, AART1 (augmented adaptive resonance theory), that describes the dynamics of the ART1 model is presented. This involves modifying the architecture of the ART1 network through the addition of a reset node and a set of inhibitory nodes in the F2 layer. Along with modifications to the differential equations describing the F1 and F2 layer nodes, these changes embody the functionality of the orienting subsystem in the ART1 model. In addition, the modifications described here allow the ART1 model to be implemented solely using a set of concurrently executing nonlinear differential equations. Thus, the AART1 network requires no external control features. Computer simulation results demonstrate the efficacy of this network.",

author = "Heileman, {Gregory L.} and Michael Georgiopoulos",

year = "1992",

language = "English (US)",

isbn = "0780301641",

series = "Proceedings. IJCNN - International Joint Conference on Neural Networks",

publisher = "Publ by IEEE",

pages = "467--472",

editor = "Anon",

booktitle = "Proceedings. IJCNN - International Joint Conference on Neural Networks",

note = "International Joint Conference on Neural Networks - IJCNN-91-Seattle ; Conference date: 08-07-1991 Through 12-07-1991",

}

TY - GEN

T1 - The augmented ART1 neural network

AU - Heileman, Gregory L.

AU - Georgiopoulos, Michael

PY - 1992

Y1 - 1992

N2 - A real-time neural network, AART1 (augmented adaptive resonance theory), that describes the dynamics of the ART1 model is presented. This involves modifying the architecture of the ART1 network through the addition of a reset node and a set of inhibitory nodes in the F2 layer. Along with modifications to the differential equations describing the F1 and F2 layer nodes, these changes embody the functionality of the orienting subsystem in the ART1 model. In addition, the modifications described here allow the ART1 model to be implemented solely using a set of concurrently executing nonlinear differential equations. Thus, the AART1 network requires no external control features. Computer simulation results demonstrate the efficacy of this network.

AB - A real-time neural network, AART1 (augmented adaptive resonance theory), that describes the dynamics of the ART1 model is presented. This involves modifying the architecture of the ART1 network through the addition of a reset node and a set of inhibitory nodes in the F2 layer. Along with modifications to the differential equations describing the F1 and F2 layer nodes, these changes embody the functionality of the orienting subsystem in the ART1 model. In addition, the modifications described here allow the ART1 model to be implemented solely using a set of concurrently executing nonlinear differential equations. Thus, the AART1 network requires no external control features. Computer simulation results demonstrate the efficacy of this network.

UR - http://www.scopus.com/inward/record.url?scp=0026630719&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0026630719&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0026630719

SN - 0780301641

T3 - Proceedings. IJCNN - International Joint Conference on Neural Networks

SP - 467

EP - 472

BT - Proceedings. IJCNN - International Joint Conference on Neural Networks

A2 - Anon, null

PB - Publ by IEEE

T2 - International Joint Conference on Neural Networks - IJCNN-91-Seattle

Y2 - 8 July 1991 through 12 July 1991

ER -

The augmented ART1 neural network

Abstract

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ASJC Scopus subject areas

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