ART1 network implementation issues

Arun Rao; Mark R. Walker; L. T. Clark; L. A. Akers

ART1 network implementation issues

Arun Rao, Mark R. Walker, L. T. Clark, L. A. Akers

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

Abstract

Adaptive resonance theory (ART) is a neural-network based clustering method developed by G. A. Carpenter and S. Grossberg (1987). Its inspiration is neurobiological and its component parts are intended to model a variety of hierarchical inference levels in the human brain. Neural networks based upon ART are capable of 'recognizing' patterns close to previously stored patterns according to some criterion, and storing patterns which are not close to already stored patterns. Two varieties of ART networks have been proposed. ART1 recognizes binary inputs and ART2 can deal with general analog inputs as well. Since the emphasis of this work is on conventional hardware implementation, ART1 is mainly discussed.

Original language	English (US)
Title of host publication	TENCON '89: Fourth IEEE Region 10 International Conference
Place of Publication	Piscataway, NJ, United States
Publisher	Publ by IEEE
Pages	462-466
Number of pages	5
State	Published - 1989
Event	4th IEEE Region 10th International Conference - TENCON '89 - Bombay, India Duration: Nov 22 1989 → Nov 24 1989

Other

Other	4th IEEE Region 10th International Conference - TENCON '89
City	Bombay, India
Period	11/22/89 → 11/24/89

ASJC Scopus subject areas

General Engineering

Cite this

@inproceedings{43b11dc6180f4e2a85bb7a163c876d6b,

title = "ART1 network implementation issues",

abstract = "Adaptive resonance theory (ART) is a neural-network based clustering method developed by G. A. Carpenter and S. Grossberg (1987). Its inspiration is neurobiological and its component parts are intended to model a variety of hierarchical inference levels in the human brain. Neural networks based upon ART are capable of 'recognizing' patterns close to previously stored patterns according to some criterion, and storing patterns which are not close to already stored patterns. Two varieties of ART networks have been proposed. ART1 recognizes binary inputs and ART2 can deal with general analog inputs as well. Since the emphasis of this work is on conventional hardware implementation, ART1 is mainly discussed.",

author = "Arun Rao and Walker, {Mark R.} and Clark, {L. T.} and Akers, {L. A.}",

year = "1989",

language = "English (US)",

pages = "462--466",

booktitle = "TENCON '89: Fourth IEEE Region 10 International Conference",

publisher = "Publ by IEEE",

note = "4th IEEE Region 10th International Conference - TENCON '89 ; Conference date: 22-11-1989 Through 24-11-1989",

}

TY - GEN

T1 - ART1 network implementation issues

AU - Rao, Arun

AU - Walker, Mark R.

AU - Clark, L. T.

AU - Akers, L. A.

PY - 1989

Y1 - 1989

N2 - Adaptive resonance theory (ART) is a neural-network based clustering method developed by G. A. Carpenter and S. Grossberg (1987). Its inspiration is neurobiological and its component parts are intended to model a variety of hierarchical inference levels in the human brain. Neural networks based upon ART are capable of 'recognizing' patterns close to previously stored patterns according to some criterion, and storing patterns which are not close to already stored patterns. Two varieties of ART networks have been proposed. ART1 recognizes binary inputs and ART2 can deal with general analog inputs as well. Since the emphasis of this work is on conventional hardware implementation, ART1 is mainly discussed.

AB - Adaptive resonance theory (ART) is a neural-network based clustering method developed by G. A. Carpenter and S. Grossberg (1987). Its inspiration is neurobiological and its component parts are intended to model a variety of hierarchical inference levels in the human brain. Neural networks based upon ART are capable of 'recognizing' patterns close to previously stored patterns according to some criterion, and storing patterns which are not close to already stored patterns. Two varieties of ART networks have been proposed. ART1 recognizes binary inputs and ART2 can deal with general analog inputs as well. Since the emphasis of this work is on conventional hardware implementation, ART1 is mainly discussed.

UR - http://www.scopus.com/inward/record.url?scp=0024774467&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0024774467&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0024774467

SP - 462

EP - 466

BT - TENCON '89: Fourth IEEE Region 10 International Conference

PB - Publ by IEEE

CY - Piscataway, NJ, United States

T2 - 4th IEEE Region 10th International Conference - TENCON '89

Y2 - 22 November 1989 through 24 November 1989

ER -

ART1 network implementation issues

Abstract

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ASJC Scopus subject areas

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