Principal Components Extraction by Autoassociative Feed-Forward Networks

Hanseok Ko; R. H. Baran

doi:10.1109/IJCNN.1992.287159

Principal Components Extraction by Autoassociative Feed-Forward Networks

Hanseok Ko, R. H. Baran

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

1 Citation (Scopus)

Abstract

We describe a methodology for testing the ability of autoassociative, feed-forward, backpropagation networks to extract the principal components from a training set. Some simple examples, treated analytically and validated by numerical trials, suggest that such behavior may be typical.

Original language	English
Title of host publication	Proceedings - 1992 International Joint Conference on Neural Networks, IJCNN 1992
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	523-528
Number of pages	6
ISBN (Electronic)	0780305590
DOIs	https://doi.org/10.1109/IJCNN.1992.287159
Publication status	Published - 1992
Externally published	Yes
Event	1992 International Joint Conference on Neural Networks, IJCNN 1992 - Baltimore, United States Duration: 1992 Jun 7 → 1992 Jun 11

Publication series

Name	Proceedings of the International Joint Conference on Neural Networks
Volume	1

Conference

Conference	1992 International Joint Conference on Neural Networks, IJCNN 1992
Country/Territory	United States
City	Baltimore
Period	92/6/7 → 92/6/11

ASJC Scopus subject areas

Software
Artificial Intelligence

Access to Document

10.1109/IJCNN.1992.287159

Cite this

Ko, H., & Baran, R. H. (1992). Principal Components Extraction by Autoassociative Feed-Forward Networks. In Proceedings - 1992 International Joint Conference on Neural Networks, IJCNN 1992 (pp. 523-528). (Proceedings of the International Joint Conference on Neural Networks; Vol. 1). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.1992.287159

Principal Components Extraction by Autoassociative Feed-Forward Networks. / Ko, Hanseok; Baran, R. H.

Proceedings - 1992 International Joint Conference on Neural Networks, IJCNN 1992. Institute of Electrical and Electronics Engineers Inc., 1992. p. 523-528 (Proceedings of the International Joint Conference on Neural Networks; Vol. 1).

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

Ko, H & Baran, RH 1992, Principal Components Extraction by Autoassociative Feed-Forward Networks. in Proceedings - 1992 International Joint Conference on Neural Networks, IJCNN 1992. Proceedings of the International Joint Conference on Neural Networks, vol. 1, Institute of Electrical and Electronics Engineers Inc., pp. 523-528, 1992 International Joint Conference on Neural Networks, IJCNN 1992, Baltimore, United States, 92/6/7. https://doi.org/10.1109/IJCNN.1992.287159

@inproceedings{dd19d2a56899473d9c7dfb0c817b39e8,

title = "Principal Components Extraction by Autoassociative Feed-Forward Networks",

abstract = "We describe a methodology for testing the ability of autoassociative, feed-forward, backpropagation networks to extract the principal components from a training set. Some simple examples, treated analytically and validated by numerical trials, suggest that such behavior may be typical.",

author = "Hanseok Ko and Baran, {R. H.}",

note = "Publisher Copyright: {\textcopyright} 1992 IEEE.; 1992 International Joint Conference on Neural Networks, IJCNN 1992 ; Conference date: 07-06-1992 Through 11-06-1992",

year = "1992",

doi = "10.1109/IJCNN.1992.287159",

language = "English",

series = "Proceedings of the International Joint Conference on Neural Networks",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "523--528",

booktitle = "Proceedings - 1992 International Joint Conference on Neural Networks, IJCNN 1992",

}

TY - GEN

T1 - Principal Components Extraction by Autoassociative Feed-Forward Networks

AU - Ko, Hanseok

AU - Baran, R. H.

PY - 1992

Y1 - 1992

N2 - We describe a methodology for testing the ability of autoassociative, feed-forward, backpropagation networks to extract the principal components from a training set. Some simple examples, treated analytically and validated by numerical trials, suggest that such behavior may be typical.

AB - We describe a methodology for testing the ability of autoassociative, feed-forward, backpropagation networks to extract the principal components from a training set. Some simple examples, treated analytically and validated by numerical trials, suggest that such behavior may be typical.

UR - http://www.scopus.com/inward/record.url?scp=84909867876&partnerID=8YFLogxK

U2 - 10.1109/IJCNN.1992.287159

DO - 10.1109/IJCNN.1992.287159

M3 - Conference contribution

AN - SCOPUS:84909867876

T3 - Proceedings of the International Joint Conference on Neural Networks

SP - 523

EP - 528

BT - Proceedings - 1992 International Joint Conference on Neural Networks, IJCNN 1992

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 1992 International Joint Conference on Neural Networks, IJCNN 1992

Y2 - 7 June 1992 through 11 June 1992

ER -

Principal Components Extraction by Autoassociative Feed-Forward Networks

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this